flair_cadec_v3_baseline.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os, random\n",
    "\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "import seaborn as sns\n",
    "import pickle\n",
    "\n",
    "from tqdm.auto import tqdm\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['meddra',\n",
       " 'meddra - unedited version of edited files',\n",
       " 'original',\n",
       " 'original - unedited version of edited files',\n",
       " 'sct',\n",
       " 'sct - unedited version of edited files',\n",
       " 'text']"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir('datasets/CADEC/CADEC.v2/cadec')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "suf = '_v3'\n",
    "\n",
    "data_save_dir = 'data'+suf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ner</th>\n",
       "      <th>meddra</th>\n",
       "      <th>counts_exploded</th>\n",
       "      <th>counts</th>\n",
       "      <th>counts_exploded_rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Drug</td>\n",
       "      <td>Lipitor</td>\n",
       "      <td>1081</td>\n",
       "      <td>1073</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADR</td>\n",
       "      <td>CONCEPT_LESS</td>\n",
       "      <td>1016</td>\n",
       "      <td>266</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Severe_pain</td>\n",
       "      <td>722</td>\n",
       "      <td>247</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Myalgia</td>\n",
       "      <td>619</td>\n",
       "      <td>305</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Pain</td>\n",
       "      <td>292</td>\n",
       "      <td>260</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1294</th>\n",
       "      <td>Finding</td>\n",
       "      <td>Senility</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1295</th>\n",
       "      <td>Drug</td>\n",
       "      <td>Seroquel</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1296</th>\n",
       "      <td>Drug</td>\n",
       "      <td>Solaraze</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1297</th>\n",
       "      <td>Drug</td>\n",
       "      <td>Tagamet</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1298</th>\n",
       "      <td>Drug</td>\n",
       "      <td>testosterone</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1299 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          ner        meddra  counts_exploded  counts  counts_exploded_rank\n",
       "0        Drug       Lipitor             1081    1073                     1\n",
       "1         ADR  CONCEPT_LESS             1016     266                     2\n",
       "2         ADR   Severe_pain              722     247                     3\n",
       "3         ADR       Myalgia              619     305                     4\n",
       "4         ADR          Pain              292     260                     5\n",
       "...       ...           ...              ...     ...                   ...\n",
       "1294  Finding      Senility                1       1                  1233\n",
       "1295     Drug      Seroquel                1       1                  1233\n",
       "1296     Drug      Solaraze                1       1                  1233\n",
       "1297     Drug       Tagamet                1       1                  1233\n",
       "1298     Drug  testosterone                1       1                  1233\n",
       "\n",
       "[1299 rows x 5 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meddra_counts = pd.read_csv(data_save_dir+'/meddra_counts.csv')\n",
    "meddra_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ner</th>\n",
       "      <th>meddra</th>\n",
       "      <th>counts_exploded</th>\n",
       "      <th>counts</th>\n",
       "      <th>counts_exploded_rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADR</td>\n",
       "      <td>CONCEPT_LESS</td>\n",
       "      <td>1016</td>\n",
       "      <td>266</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Severe_pain</td>\n",
       "      <td>722</td>\n",
       "      <td>247</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Myalgia</td>\n",
       "      <td>619</td>\n",
       "      <td>305</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Pain</td>\n",
       "      <td>292</td>\n",
       "      <td>260</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Arthralgia</td>\n",
       "      <td>280</td>\n",
       "      <td>163</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>1268</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Labyrinthitis</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1269</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Dysphagia</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1275</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Lupus_erythematosus</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1278</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Cataract</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>ADR</td>\n",
       "      <td>Crying_associated_with_mood</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1233</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>800 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      ner                       meddra  counts_exploded  counts   \n",
       "1     ADR                 CONCEPT_LESS             1016     266  \\\n",
       "2     ADR                  Severe_pain              722     247   \n",
       "3     ADR                      Myalgia              619     305   \n",
       "4     ADR                         Pain              292     260   \n",
       "5     ADR                   Arthralgia              280     163   \n",
       "...   ...                          ...              ...     ...   \n",
       "1268  ADR                Labyrinthitis                1       1   \n",
       "1269  ADR                    Dysphagia                1       1   \n",
       "1275  ADR          Lupus_erythematosus                1       1   \n",
       "1278  ADR                     Cataract                1       1   \n",
       "1283  ADR  Crying_associated_with_mood                1       1   \n",
       "\n",
       "      counts_exploded_rank  \n",
       "1                        2  \n",
       "2                        3  \n",
       "3                        4  \n",
       "4                        5  \n",
       "5                        6  \n",
       "...                    ...  \n",
       "1268                  1233  \n",
       "1269                  1233  \n",
       "1275                  1233  \n",
       "1278                  1233  \n",
       "1283                  1233  \n",
       "\n",
       "[800 rows x 5 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meddra_counts.loc[meddra_counts.ner == 'ADR',:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Sentence[117]: \"i feel a bit drowsy & have a little blurred vision , so far no gastric problems . ive been on arthrotec 50 for over 10 years on and off , only taking it when i needed it . due to my arthritis getting progressively worse , to the point where i am in tears with the agony , gp ' s started me on 75 twice a day and i have to take it . every day for the next month to see how i get on , here goes . so far its been very good , pains almost gone , but i feel a bit weird , didnt have that when on 50 .\" → [\"i\"/O/O, \"feel\"/O/O, \"a\"/O/O, \"bit\"/B-ADR/B-Drowsy, \"drowsy\"/I-ADR/I-Drowsy, \"&\"/O/O, \"have\"/O/O, \"a\"/O/O, \"little\"/B-ADR/B-Blurred_vision_-_hazy, \"blurred\"/I-ADR/I-Blurred_vision_-_hazy, \"vision\"/I-ADR/I-Blurred_vision_-_hazy, \",\"/O/O, \"so\"/O/O, \"far\"/O/O, \"no\"/O/O, \"gastric\"/B-ADR/B-Excessive_upper_gastrointestinal_gas, \"problems\"/I-ADR/I-Excessive_upper_gastrointestinal_gas, \".\"/O/O, \"ive\"/O/O, \"been\"/O/O, \"on\"/O/O, \"arthrotec\"/B-Drug/B-Arthrotec, \"50\"/O/O, \"for\"/O/O, \"over\"/O/O, \"10\"/O/O, \"years\"/O/O, \"on\"/O/O, \"and\"/O/O, \"off\"/O/O, \",\"/O/O, \"only\"/O/O, \"taking\"/O/O, \"it\"/O/O, \"when\"/O/O, \"i\"/O/O, \"needed\"/O/O, \"it\"/O/O, \".\"/O/O, \"due\"/O/O, \"to\"/O/O, \"my\"/O/O, \"arthritis\"/B-Disease/B-Arthritis, \"getting\"/O/O, \"progressively\"/O/O, \"worse\"/O/O, \",\"/O/O, \"to\"/O/O, \"the\"/O/O, \"point\"/O/O, \"where\"/O/O, \"i\"/O/O, \"am\"/O/O, \"in\"/O/O, \"tears\"/O/O, \"with\"/O/O, \"the\"/O/O, \"agony\"/B-Symptom/B-Agony, \",\"/O/O, \"gp\"/O/O, \"'\"/O/O, \"s\"/O/O, \"started\"/O/O, \"me\"/O/O, \"on\"/O/O, \"75\"/O/O, \"twice\"/O/O, \"a\"/O/O, \"day\"/O/O, \"and\"/O/O, \"i\"/O/O, \"have\"/O/O, \"to\"/O/O, \"take\"/O/O, \"it\"/O/O, \".\"/O/O, \"every\"/O/O, \"day\"/O/O, \"for\"/O/O, \"the\"/O/O, \"next\"/O/O, \"month\"/O/O, \"to\"/O/O, \"see\"/O/O, \"how\"/O/O, \"i\"/O/O, \"get\"/O/O, \"on\"/O/O, \",\"/O/O, \"here\"/O/O, \"goes\"/O/O, \".\"/O/O, \"so\"/O/O, \"far\"/O/O, \"its\"/O/O, \"been\"/O/O, \"very\"/O/O, \"good\"/O/O, \",\"/O/O, \"pains\"/B-Symptom/B-Pain, \"almost\"/O/O, \"gone\"/O/O, \",\"/O/O, \"but\"/O/O, \"i\"/O/O, \"feel\"/B-ADR/B-Malaise, \"a\"/I-ADR/I-Malaise, \"bit\"/I-ADR/I-Malaise, \"weird\"/I-ADR/I-Malaise, \",\"/O/O, \"didnt\"/O/O, \"have\"/O/O, \"that\"/O/O, \"when\"/O/O, \"on\"/O/O, \"50\"/O/O, \".\"/O/O],\n",
       " Sentence[39]: \"hunger pangs . brilliant , i have a new lease of life , i walk up & down steps properly , no longer sideways like a toddler , hip pain as gone other than if i jar it .\" → [\"hunger\"/B-ADR/B-Hunger_pain, \"pangs\"/I-ADR/I-Hunger_pain, \".\"/O/O, \"brilliant\"/O/O, \",\"/O/O, \"i\"/O/O, \"have\"/O/O, \"a\"/O/O, \"new\"/O/O, \"lease\"/O/O, \"of\"/O/O, \"life\"/O/O, \",\"/O/O, \"i\"/O/O, \"walk\"/B-Symptom/B-CONCEPT_LESS, \"up\"/I-Symptom/I-CONCEPT_LESS, \"&\"/I-Symptom/I-CONCEPT_LESS, \"down\"/I-Symptom/I-CONCEPT_LESS, \"steps\"/I-Symptom/I-CONCEPT_LESS, \"properly\"/O/O, \",\"/O/O, \"no\"/O/O, \"longer\"/O/O, \"sideways\"/I-Symptom/I-CONCEPT_LESS, \"like\"/O/O, \"a\"/O/O, \"toddler\"/O/O, \",\"/O/O, \"hip\"/B-Symptom/B-Hip_pain, \"pain\"/I-Symptom/I-Hip_pain, \"as\"/O/O, \"gone\"/O/O, \"other\"/O/O, \"than\"/O/O, \"if\"/O/O, \"i\"/O/O, \"jar\"/O/O, \"it\"/O/O, \".\"/O/O],\n",
       " Sentence[51]: \"no side effects for the first two months . then vaginal bleeding 2 wks after menstral cycle . stomach pain . canker sores in my mouth . headache . been off for 1 week still have bleeding . helped my pain alot . too scared to take this drug again .\" → [\"no\"/O/O, \"side\"/O/O, \"effects\"/O/O, \"for\"/O/O, \"the\"/O/O, \"first\"/O/O, \"two\"/O/O, \"months\"/O/O, \".\"/O/O, \"then\"/O/O, \"vaginal\"/B-ADR/B-Vaginal_bleeding, \"bleeding\"/I-ADR/I-Vaginal_bleeding, \"2\"/O/O, \"wks\"/O/O, \"after\"/O/O, \"menstral\"/O/O, \"cycle\"/O/O, \".\"/O/O, \"stomach\"/B-ADR/B-Stomach_ache, \"pain\"/I-ADR/I-Stomach_ache, \".\"/O/O, \"canker\"/B-ADR/B-Aphthous_ulcer, \"sores\"/I-ADR/I-Aphthous_ulcer, \"in\"/O/O, \"my\"/O/O, \"mouth\"/O/O, \".\"/O/O, \"headache\"/B-ADR/B-Headache, \".\"/O/O, \"been\"/O/O, \"off\"/O/O, \"for\"/O/O, \"1\"/O/O, \"week\"/O/O, \"still\"/O/O, \"have\"/O/O, \"bleeding\"/O/O, \".\"/O/O, \"helped\"/O/O, \"my\"/O/O, \"pain\"/B-Symptom/B-Pain, \"alot\"/O/O, \".\"/O/O, \"too\"/O/O, \"scared\"/O/O, \"to\"/O/O, \"take\"/O/O, \"this\"/O/O, \"drug\"/O/O, \"again\"/O/O, \".\"/O/O],\n",
       " Sentence[68]: \"1st pill taken with food , a few hours after i experienced shortness of breath , a sense of depression , cramping , upset stomache will stop taking immediately . honestly can not recommend this drug , i am still experiencing side effects just after 1 pill and im supposed to take twice / day 75mg . i just cant keep going have to try something else .\" → [\"1st\"/O/O, \"pill\"/O/O, \"taken\"/O/O, \"with\"/O/O, \"food\"/O/O, \",\"/O/O, \"a\"/O/O, \"few\"/O/O, \"hours\"/O/O, \"after\"/O/O, \"i\"/O/O, \"experienced\"/O/O, \"shortness\"/B-ADR/B-Dyspnoea, \"of\"/I-ADR/I-Dyspnoea, \"breath\"/I-ADR/I-Dyspnoea, \",\"/O/O, \"a\"/O/O, \"sense\"/O/O, \"of\"/O/O, \"depression\"/B-ADR/B-Depression, \",\"/O/O, \"cramping\"/B-ADR/B-Muscle_cramp, \",\"/O/O, \"upset\"/B-ADR/B-Upset_stomach, \"stomache\"/I-ADR/I-Upset_stomach, \"will\"/O/O, \"stop\"/O/O, \"taking\"/O/O, \"immediately\"/O/O, \".\"/O/O, \"honestly\"/O/O, \"can\"/O/O, \"not\"/O/O, \"recommend\"/O/O, \"this\"/O/O, \"drug\"/O/O, \",\"/O/O, \"i\"/O/O, \"am\"/O/O, \"still\"/O/O, \"experiencing\"/O/O, \"side\"/O/O, \"effects\"/O/O, \"just\"/O/O, \"after\"/O/O, \"1\"/O/O, \"pill\"/O/O, \"and\"/O/O, \"im\"/O/O, \"supposed\"/O/O, \"to\"/O/O, \"take\"/O/O, \"twice\"/O/O, \"/\"/O/O, \"day\"/O/O, \"75mg\"/O/O, \".\"/O/O, \"i\"/O/O, \"just\"/O/O, \"cant\"/O/O, \"keep\"/O/O, \"going\"/O/O, \"have\"/O/O, \"to\"/O/O, \"try\"/O/O, \"something\"/O/O, \"else\"/O/O, \".\"/O/O],\n",
       " Sentence[50]: \"i have had no side effects been taking arthrotec a little over a year , have not noticed any side effects . it does help alot i noticed that when there are times when i forget to take it i cant stand or walk for any lengths of time .\" → [\"i\"/O/O, \"have\"/O/O, \"had\"/O/O, \"no\"/O/O, \"side\"/O/O, \"effects\"/O/O, \"been\"/O/O, \"taking\"/O/O, \"arthrotec\"/B-Drug/B-Arthrotec, \"a\"/O/O, \"little\"/O/O, \"over\"/O/O, \"a\"/O/O, \"year\"/O/O, \",\"/O/O, \"have\"/O/O, \"not\"/O/O, \"noticed\"/O/O, \"any\"/O/O, \"side\"/O/O, \"effects\"/O/O, \".\"/O/O, \"it\"/O/O, \"does\"/O/O, \"help\"/O/O, \"alot\"/O/O, \"i\"/O/O, \"noticed\"/O/O, \"that\"/O/O, \"when\"/O/O, \"there\"/O/O, \"are\"/O/O, \"times\"/O/O, \"when\"/O/O, \"i\"/O/O, \"forget\"/O/O, \"to\"/O/O, \"take\"/O/O, \"it\"/O/O, \"i\"/B-Symptom/B-Reduced_mobility, \"cant\"/I-Symptom/I-Reduced_mobility, \"stand\"/I-Symptom/I-Reduced_mobility, \"or\"/I-Symptom/I-Reduced_mobility, \"walk\"/I-Symptom/I-Reduced_mobility, \"for\"/I-Symptom/I-Reduced_mobility, \"any\"/I-Symptom/I-Reduced_mobility, \"lengths\"/I-Symptom/I-Reduced_mobility, \"of\"/I-Symptom/I-Reduced_mobility, \"time\"/I-Symptom/I-Reduced_mobility, \".\"/O/O],\n",
       " Sentence[89]: \"it seems as if bleeding forever is a side effect but doctors tell you that its not the drug . i have been on arthotec for three months i still have pain and stiffness . at first week into this drug i was in so much pain i sat on the floor at work and thought i was gaving a baby . i always feel weak and almost fainted a bunch of times . consider somthing that works i am switching today as this isnt in my head .\" → [\"it\"/O/O, \"seems\"/O/O, \"as\"/O/O, \"if\"/O/O, \"bleeding\"/B-ADR/B-Bleeding, \"forever\"/O/O, \"is\"/O/O, \"a\"/O/O, \"side\"/O/O, \"effect\"/O/O, \"but\"/O/O, \"doctors\"/O/O, \"tell\"/O/O, \"you\"/O/O, \"that\"/O/O, \"its\"/O/O, \"not\"/O/O, \"the\"/O/O, \"drug\"/O/O, \".\"/O/O, \"i\"/O/O, \"have\"/O/O, \"been\"/O/O, \"on\"/O/O, \"arthotec\"/B-Drug/B-Arthrotec, \"for\"/O/O, \"three\"/O/O, \"months\"/O/O, \"i\"/O/O, \"still\"/O/O, \"have\"/O/O, \"pain\"/B-Symptom/B-Pain, \"and\"/I-Symptom/I-Pain, \"stiffness\"/I-Symptom/I-Pain, \".\"/O/O, \"at\"/O/O, \"first\"/O/O, \"week\"/O/O, \"into\"/O/O, \"this\"/O/O, \"drug\"/O/O, \"i\"/O/O, \"was\"/O/O, \"in\"/O/O, \"so\"/B-ADR/B-Pain, \"much\"/I-ADR/I-Pain, \"pain\"/I-ADR/I-Pain, \"i\"/O/O, \"sat\"/O/O, \"on\"/O/O, \"the\"/O/O, \"floor\"/O/O, \"at\"/O/O, \"work\"/O/O, \"and\"/O/O, \"thought\"/O/O, \"i\"/O/O, \"was\"/O/O, \"gaving\"/O/O, \"a\"/O/O, \"baby\"/O/O, \".\"/O/O, \"i\"/O/O, \"always\"/O/O, \"feel\"/B-ADR/B-Malaise_and_fatigue, \"weak\"/I-ADR/I-Malaise_and_fatigue, \"and\"/I-ADR/I-Malaise_and_fatigue, \"almost\"/I-ADR/I-Malaise_and_fatigue, \"fainted\"/I-ADR/I-Malaise_and_fatigue, \"a\"/O/O, \"bunch\"/O/O, \"of\"/O/O, \"times\"/O/O, \".\"/O/O, \"consider\"/O/O, \"somthing\"/O/O, \"that\"/O/O, \"works\"/O/O, \"i\"/O/O, \"am\"/O/O, \"switching\"/O/O, \"today\"/O/O, \"as\"/O/O, \"this\"/O/O, \"isnt\"/O/O, \"in\"/O/O, \"my\"/O/O, \"head\"/O/O, \".\"/O/O],\n",
       " Sentence[56]: \"some diarrhea , some constipation , fatigue . it works very well for the heel ; i couldnt walk on it very well before taking it . i take 75mg . twice a day . also have severe osteoarthritis in the knees and hands , but it doesnt seem to relieve that pain at all .\" → [\"some\"/O/O, \"diarrhea\"/B-ADR/B-Diarrhoea, \",\"/O/O, \"some\"/O/O, \"constipation\"/B-ADR/B-Constipation, \",\"/O/O, \"fatigue\"/B-ADR/B-Fatigue, \".\"/O/O, \"it\"/O/O, \"works\"/O/O, \"very\"/O/O, \"well\"/O/O, \"for\"/O/O, \"the\"/B-Symptom/B-Walking_disability, \"heel\"/I-Symptom/I-Walking_disability, \";\"/O/O, \"i\"/I-Symptom/I-Walking_disability, \"couldnt\"/I-Symptom/I-Walking_disability, \"walk\"/I-Symptom/I-Walking_disability, \"on\"/I-Symptom/I-Walking_disability, \"it\"/O/O, \"very\"/I-Symptom/I-Walking_disability, \"well\"/I-Symptom/I-Walking_disability, \"before\"/O/O, \"taking\"/O/O, \"it\"/O/O, \".\"/O/O, \"i\"/O/O, \"take\"/O/O, \"75mg\"/O/O, \".\"/O/O, \"twice\"/O/O, \"a\"/O/O, \"day\"/O/O, \".\"/O/O, \"also\"/O/O, \"have\"/O/O, \"severe\"/B-Disease/B-Osteoarthritis_of_knee/B-Osteoarthrosis_of_hand, \"osteoarthritis\"/I-Disease/I-Osteoarthritis_of_knee/I-Osteoarthrosis_of_hand, \"in\"/I-Disease/I-Osteoarthritis_of_knee/I-Osteoarthrosis_of_hand, \"the\"/I-Disease/I-Osteoarthritis_of_knee/I-Osteoarthrosis_of_hand, \"knees\"/I-Disease/I-Osteoarthritis_of_knee, \"and\"/O/O, \"hands\"/I-Disease/I-Osteoarthrosis_of_hand, \",\"/O/O, \"but\"/O/O, \"it\"/O/O, \"doesnt\"/O/O, \"seem\"/O/O, \"to\"/O/O, \"relieve\"/O/O, \"that\"/O/O, \"pain\"/B-Symptom/B-Pain, \"at\"/O/O, \"all\"/O/O, \".\"/O/O],\n",
       " Sentence[84]: \"ive been on 75mg twice daily for 13 days , with recent body swelling , face , wrists , abdomen , thighs - clothes fit tight . insomina is much worse . i have forgetfulnes and confussion - really bad - almost dangerous . have felt \" empty stomach \" feeling , but not bothersome . have had more loose stools , but tolerable . im looking for a more natural therapy , checking into ha ( hyaluronic acid ) to replace arthrotec .\" → [\"ive\"/O/O, \"been\"/O/O, \"on\"/O/O, \"75mg\"/O/O, \"twice\"/O/O, \"daily\"/O/O, \"for\"/O/O, \"13\"/O/O, \"days\"/O/O, \",\"/O/O, \"with\"/O/O, \"recent\"/O/O, \"body\"/B-ADR/B-Swelling_of_body_region, \"swelling\"/B-ADR/I-ADR/B-Abdominal_swelling/B-Facial_swelling/I-Swelling_of_body_region/B-Swelling_of_lower_limb/B-Swelling_of_wrist_joint, \",\"/O/O, \"face\"/I-ADR/I-Facial_swelling, \",\"/O/O, \"wrists\"/I-ADR/I-Swelling_of_wrist_joint, \",\"/O/O, \"abdomen\"/I-ADR/I-Abdominal_swelling, \",\"/O/O, \"thighs\"/I-ADR/I-Swelling_of_lower_limb, \"-\"/O/O, \"clothes\"/O/O, \"fit\"/O/O, \"tight\"/O/O, \".\"/O/O, \"insomina\"/B-ADR/B-Insomnia, \"is\"/O/O, \"much\"/O/O, \"worse\"/O/O, \".\"/O/O, \"i\"/O/O, \"have\"/O/O, \"forgetfulnes\"/B-ADR/B-Forgetful, \"and\"/I-ADR/I-Forgetful, \"confussion\"/I-ADR/I-Forgetful, \"-\"/O/O, \"really\"/O/O, \"bad\"/O/O, \"-\"/O/O, \"almost\"/O/O, \"dangerous\"/O/O, \".\"/O/O, \"have\"/O/O, \"felt\"/O/O, \"\"\"/B-ADR/B-Feeling_empty, \"empty\"/I-ADR/I-Feeling_empty, \"stomach\"/I-ADR/I-Feeling_empty, \"\"\"/I-ADR/I-Feeling_empty, \"feeling\"/I-ADR/I-Feeling_empty, \",\"/O/O, \"but\"/O/O, \"not\"/O/O, \"bothersome\"/O/O, \".\"/O/O, \"have\"/O/O, \"had\"/O/O, \"more\"/O/O, \"loose\"/B-ADR/B-Loose_stool, \"stools\"/I-ADR/I-Loose_stool, \",\"/O/O, \"but\"/O/O, \"tolerable\"/O/O, \".\"/O/O, \"im\"/O/O, \"looking\"/O/O, \"for\"/O/O, \"a\"/O/O, \"more\"/O/O, \"natural\"/O/O, \"therapy\"/O/O, \",\"/O/O, \"checking\"/O/O, \"into\"/O/O, \"ha\"/B-Drug/B-CONCEPT_LESS, \"(\"/I-Drug/I-CONCEPT_LESS, \"hyaluronic\"/I-Drug/I-CONCEPT_LESS, \"acid\"/I-Drug/I-CONCEPT_LESS, \")\"/I-Drug/I-CONCEPT_LESS, \"to\"/O/O, \"replace\"/O/O, \"arthrotec\"/B-Drug/B-Arthrotec, \".\"/O/O],\n",
       " Sentence[68]: \"none that i can think of . i recently had bilateral knee replacement . prior to that , arthrotec was the only drug that helped . i tried every drug on the market , but , to no avail . i took 50 mg . 3 times a day of arthrotec and was almost pain free . i highly recommend it to anyone that suffers from arthritis .\" → [\"none\"/O/O, \"that\"/O/O, \"i\"/O/O, \"can\"/O/O, \"think\"/O/O, \"of\"/O/O, \".\"/O/O, \"i\"/O/O, \"recently\"/O/O, \"had\"/O/O, \"bilateral\"/O/O, \"knee\"/O/O, \"replacement\"/O/O, \".\"/O/O, \"prior\"/O/O, \"to\"/O/O, \"that\"/O/O, \",\"/O/O, \"arthrotec\"/B-Drug/B-Arthrotec, \"was\"/O/O, \"the\"/O/O, \"only\"/O/O, \"drug\"/O/O, \"that\"/O/O, \"helped\"/O/O, \".\"/O/O, \"i\"/O/O, \"tried\"/O/O, \"every\"/O/O, \"drug\"/O/O, \"on\"/O/O, \"the\"/O/O, \"market\"/O/O, \",\"/O/O, \"but\"/O/O, \",\"/O/O, \"to\"/O/O, \"no\"/O/O, \"avail\"/O/O, \".\"/O/O, \"i\"/O/O, \"took\"/O/O, \"50\"/O/O, \"mg\"/O/O, \".\"/O/O, \"3\"/O/O, \"times\"/O/O, \"a\"/O/O, \"day\"/O/O, \"of\"/O/O, \"arthrotec\"/B-Drug/B-Arthrotec, \"and\"/O/O, \"was\"/O/O, \"almost\"/O/O, \"pain\"/B-Symptom/B-Pain, \"free\"/O/O, \".\"/O/O, \"i\"/O/O, \"highly\"/O/O, \"recommend\"/O/O, \"it\"/O/O, \"to\"/O/O, \"anyone\"/O/O, \"that\"/O/O, \"suffers\"/O/O, \"from\"/O/O, \"arthritis\"/B-Finding/B-Arthritis, \".\"/O/O],\n",
       " Sentence[28]: \"hospitalization due extreme rectal bleed that required blood transfusion . i was extremely sick and initially felt i might not survive . should be removed from market .\" → [\"hospitalization\"/O/O, \"due\"/O/O, \"extreme\"/O/O, \"rectal\"/B-ADR/B-Rectal_haemorrhage, \"bleed\"/I-ADR/I-Rectal_haemorrhage, \"that\"/O/O, \"required\"/O/O, \"blood\"/O/O, \"transfusion\"/O/O, \".\"/O/O, \"i\"/O/O, \"was\"/O/O, \"extremely\"/B-ADR/B-Generally_unwell, \"sick\"/I-ADR/I-Generally_unwell, \"and\"/O/O, \"initially\"/O/O, \"felt\"/B-ADR/B-CONCEPT_LESS, \"i\"/I-ADR/I-CONCEPT_LESS, \"might\"/I-ADR/I-CONCEPT_LESS, \"not\"/I-ADR/I-CONCEPT_LESS, \"survive\"/I-ADR/I-CONCEPT_LESS, \".\"/O/O, \"should\"/O/O, \"be\"/O/O, \"removed\"/O/O, \"from\"/O/O, \"market\"/O/O, \".\"/O/O]]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with open(data_save_dir+'/cadec_flair_objects.pkl', 'rb') as f:\n",
    "    docs = pickle.load(f)\n",
    "docs[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1186"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(docs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method Sentence.to_plain_string of Sentence[157]: \"wow , so im not crazy after all ! my dr cant seem to find out why my feet hurt in the morning and unexplained joint pain , i get even after just sitting for an hour watching tv in the evening . man i get up and i can hardly walk . stiffness in my feet , and leg joint . dr has done x - ray and everything . im think he is thinking it is in my head all this pain . now when i so called sleep at night i have been noticing i get numbness in my hands , and it isnt due to me lying on my arms or anything , and my lt wrist joint , where my thumb is attached , is dislocating or it painfully sticks . and i have to painfully put it back in . im going to show this website to my gp ! .\" → [\"wow\"/O/O, \",\"/O/O, \"so\"/O/O, \"im\"/O/O, \"not\"/O/O, \"crazy\"/O/O, \"after\"/O/O, \"all\"/O/O, \"!\"/O/O, \"my\"/O/O, \"dr\"/O/O, \"cant\"/O/O, \"seem\"/O/O, \"to\"/O/O, \"find\"/O/O, \"out\"/O/O, \"why\"/O/O, \"my\"/O/O, \"feet\"/B-ADR/B-Foot_pain, \"hurt\"/I-ADR/I-Foot_pain, \"in\"/O/O, \"the\"/O/O, \"morning\"/O/O, \"and\"/O/O, \"unexplained\"/O/O, \"joint\"/B-ADR/B-Arthralgia, \"pain\"/I-ADR/I-Arthralgia, \",\"/O/O, \"i\"/O/O, \"get\"/O/O, \"even\"/O/O, \"after\"/O/O, \"just\"/O/O, \"sitting\"/O/O, \"for\"/O/O, \"an\"/O/O, \"hour\"/O/O, \"watching\"/O/O, \"tv\"/O/O, \"in\"/O/O, \"the\"/O/O, \"evening\"/O/O, \".\"/O/O, \"man\"/O/O, \"i\"/O/O, \"get\"/O/O, \"up\"/O/O, \"and\"/O/O, \"i\"/O/O, \"can\"/B-ADR/B-Walking_disability, \"hardly\"/I-ADR/I-Walking_disability, \"walk\"/I-ADR/I-Walking_disability, \".\"/O/O, \"stiffness\"/B-ADR/B-Stiff_legs, \"in\"/I-ADR/I-Stiff_legs, \"my\"/I-ADR/I-Stiff_legs, \"feet\"/I-ADR/I-Stiff_legs, \",\"/O/O, \"and\"/O/O, \"leg\"/I-ADR/I-Stiff_legs, \"joint\"/I-ADR/I-Stiff_legs, \".\"/O/O, \"dr\"/O/O, \"has\"/O/O, \"done\"/O/O, \"x\"/O/O, \"-\"/O/O, \"ray\"/O/O, \"and\"/O/O, \"everything\"/O/O, \".\"/O/O, \"im\"/O/O, \"think\"/O/O, \"he\"/O/O, \"is\"/O/O, \"thinking\"/O/O, \"it\"/O/O, \"is\"/O/O, \"in\"/O/O, \"my\"/O/O, \"head\"/O/O, \"all\"/O/O, \"this\"/O/O, \"pain\"/B-ADR/B-Pain, \".\"/O/O, \"now\"/O/O, \"when\"/O/O, \"i\"/O/O, \"so\"/O/O, \"called\"/O/O, \"sleep\"/O/O, \"at\"/O/O, \"night\"/O/O, \"i\"/O/O, \"have\"/O/O, \"been\"/O/O, \"noticing\"/O/O, \"i\"/O/O, \"get\"/O/O, \"numbness\"/B-ADR/B-Numbness_of_hand, \"in\"/I-ADR/I-Numbness_of_hand, \"my\"/I-ADR/I-Numbness_of_hand, \"hands\"/I-ADR/I-Numbness_of_hand, \",\"/O/O, \"and\"/O/O, \"it\"/O/O, \"isnt\"/O/O, \"due\"/O/O, \"to\"/O/O, \"me\"/O/O, \"lying\"/O/O, \"on\"/O/O, \"my\"/O/O, \"arms\"/O/O, \"or\"/O/O, \"anything\"/O/O, \",\"/O/O, \"and\"/O/O, \"my\"/O/O, \"lt\"/B-ADR/B-CONCEPT_LESS, \"wrist\"/I-ADR/I-CONCEPT_LESS, \"joint\"/I-ADR/I-CONCEPT_LESS, \",\"/O/O, \"where\"/O/O, \"my\"/O/O, \"thumb\"/O/O, \"is\"/O/O, \"attached\"/O/O, \",\"/O/O, \"is\"/O/O, \"dislocating\"/B-ADR/B-Dislocation_of_joint, \"or\"/O/O, \"it\"/O/O, \"painfully\"/O/O, \"sticks\"/O/O, \".\"/O/O, \"and\"/O/O, \"i\"/O/O, \"have\"/O/O, \"to\"/O/O, \"painfully\"/O/O, \"put\"/O/O, \"it\"/O/O, \"back\"/O/O, \"in\"/O/O, \".\"/O/O, \"im\"/O/O, \"going\"/O/O, \"to\"/O/O, \"show\"/O/O, \"this\"/O/O, \"website\"/O/O, \"to\"/O/O, \"my\"/O/O, \"gp\"/O/O, \"!\"/O/O, \".\"/O/O]>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = docs[433]\n",
    "temp.to_plain_string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ner': ['Token[0]: \"wow\"'/'O' (1.0),\n",
       "  'Token[1]: \",\"'/'O' (1.0),\n",
       "  'Token[2]: \"so\"'/'O' (1.0),\n",
       "  'Token[3]: \"im\"'/'O' (1.0),\n",
       "  'Token[4]: \"not\"'/'O' (1.0),\n",
       "  'Token[5]: \"crazy\"'/'O' (1.0),\n",
       "  'Token[6]: \"after\"'/'O' (1.0),\n",
       "  'Token[7]: \"all\"'/'O' (1.0),\n",
       "  'Token[8]: \"!\"'/'O' (1.0),\n",
       "  'Token[9]: \"my\"'/'O' (1.0),\n",
       "  'Token[10]: \"dr\"'/'O' (1.0),\n",
       "  'Token[11]: \"cant\"'/'O' (1.0),\n",
       "  'Token[12]: \"seem\"'/'O' (1.0),\n",
       "  'Token[13]: \"to\"'/'O' (1.0),\n",
       "  'Token[14]: \"find\"'/'O' (1.0),\n",
       "  'Token[15]: \"out\"'/'O' (1.0),\n",
       "  'Token[16]: \"why\"'/'O' (1.0),\n",
       "  'Token[17]: \"my\"'/'O' (1.0),\n",
       "  'Token[18]: \"feet\"'/'B-ADR' (1.0),\n",
       "  'Token[19]: \"hurt\"'/'I-ADR' (1.0),\n",
       "  'Token[20]: \"in\"'/'O' (1.0),\n",
       "  'Token[21]: \"the\"'/'O' (1.0),\n",
       "  'Token[22]: \"morning\"'/'O' (1.0),\n",
       "  'Token[23]: \"and\"'/'O' (1.0),\n",
       "  'Token[24]: \"unexplained\"'/'O' (1.0),\n",
       "  'Token[25]: \"joint\"'/'B-ADR' (1.0),\n",
       "  'Token[26]: \"pain\"'/'I-ADR' (1.0),\n",
       "  'Token[27]: \",\"'/'O' (1.0),\n",
       "  'Token[28]: \"i\"'/'O' (1.0),\n",
       "  'Token[29]: \"get\"'/'O' (1.0),\n",
       "  'Token[30]: \"even\"'/'O' (1.0),\n",
       "  'Token[31]: \"after\"'/'O' (1.0),\n",
       "  'Token[32]: \"just\"'/'O' (1.0),\n",
       "  'Token[33]: \"sitting\"'/'O' (1.0),\n",
       "  'Token[34]: \"for\"'/'O' (1.0),\n",
       "  'Token[35]: \"an\"'/'O' (1.0),\n",
       "  'Token[36]: \"hour\"'/'O' (1.0),\n",
       "  'Token[37]: \"watching\"'/'O' (1.0),\n",
       "  'Token[38]: \"tv\"'/'O' (1.0),\n",
       "  'Token[39]: \"in\"'/'O' (1.0),\n",
       "  'Token[40]: \"the\"'/'O' (1.0),\n",
       "  'Token[41]: \"evening\"'/'O' (1.0),\n",
       "  'Token[42]: \".\"'/'O' (1.0),\n",
       "  'Token[43]: \"man\"'/'O' (1.0),\n",
       "  'Token[44]: \"i\"'/'O' (1.0),\n",
       "  'Token[45]: \"get\"'/'O' (1.0),\n",
       "  'Token[46]: \"up\"'/'O' (1.0),\n",
       "  'Token[47]: \"and\"'/'O' (1.0),\n",
       "  'Token[48]: \"i\"'/'O' (1.0),\n",
       "  'Token[49]: \"can\"'/'B-ADR' (1.0),\n",
       "  'Token[50]: \"hardly\"'/'I-ADR' (1.0),\n",
       "  'Token[51]: \"walk\"'/'I-ADR' (1.0),\n",
       "  'Token[52]: \".\"'/'O' (1.0),\n",
       "  'Token[53]: \"stiffness\"'/'B-ADR' (1.0),\n",
       "  'Token[54]: \"in\"'/'I-ADR' (1.0),\n",
       "  'Token[55]: \"my\"'/'I-ADR' (1.0),\n",
       "  'Token[56]: \"feet\"'/'I-ADR' (1.0),\n",
       "  'Token[57]: \",\"'/'O' (1.0),\n",
       "  'Token[58]: \"and\"'/'O' (1.0),\n",
       "  'Token[59]: \"leg\"'/'I-ADR' (1.0),\n",
       "  'Token[60]: \"joint\"'/'I-ADR' (1.0),\n",
       "  'Token[61]: \".\"'/'O' (1.0),\n",
       "  'Token[62]: \"dr\"'/'O' (1.0),\n",
       "  'Token[63]: \"has\"'/'O' (1.0),\n",
       "  'Token[64]: \"done\"'/'O' (1.0),\n",
       "  'Token[65]: \"x\"'/'O' (1.0),\n",
       "  'Token[66]: \"-\"'/'O' (1.0),\n",
       "  'Token[67]: \"ray\"'/'O' (1.0),\n",
       "  'Token[68]: \"and\"'/'O' (1.0),\n",
       "  'Token[69]: \"everything\"'/'O' (1.0),\n",
       "  'Token[70]: \".\"'/'O' (1.0),\n",
       "  'Token[71]: \"im\"'/'O' (1.0),\n",
       "  'Token[72]: \"think\"'/'O' (1.0),\n",
       "  'Token[73]: \"he\"'/'O' (1.0),\n",
       "  'Token[74]: \"is\"'/'O' (1.0),\n",
       "  'Token[75]: \"thinking\"'/'O' (1.0),\n",
       "  'Token[76]: \"it\"'/'O' (1.0),\n",
       "  'Token[77]: \"is\"'/'O' (1.0),\n",
       "  'Token[78]: \"in\"'/'O' (1.0),\n",
       "  'Token[79]: \"my\"'/'O' (1.0),\n",
       "  'Token[80]: \"head\"'/'O' (1.0),\n",
       "  'Token[81]: \"all\"'/'O' (1.0),\n",
       "  'Token[82]: \"this\"'/'O' (1.0),\n",
       "  'Token[83]: \"pain\"'/'B-ADR' (1.0),\n",
       "  'Token[84]: \".\"'/'O' (1.0),\n",
       "  'Token[85]: \"now\"'/'O' (1.0),\n",
       "  'Token[86]: \"when\"'/'O' (1.0),\n",
       "  'Token[87]: \"i\"'/'O' (1.0),\n",
       "  'Token[88]: \"so\"'/'O' (1.0),\n",
       "  'Token[89]: \"called\"'/'O' (1.0),\n",
       "  'Token[90]: \"sleep\"'/'O' (1.0),\n",
       "  'Token[91]: \"at\"'/'O' (1.0),\n",
       "  'Token[92]: \"night\"'/'O' (1.0),\n",
       "  'Token[93]: \"i\"'/'O' (1.0),\n",
       "  'Token[94]: \"have\"'/'O' (1.0),\n",
       "  'Token[95]: \"been\"'/'O' (1.0),\n",
       "  'Token[96]: \"noticing\"'/'O' (1.0),\n",
       "  'Token[97]: \"i\"'/'O' (1.0),\n",
       "  'Token[98]: \"get\"'/'O' (1.0),\n",
       "  'Token[99]: \"numbness\"'/'B-ADR' (1.0),\n",
       "  'Token[100]: \"in\"'/'I-ADR' (1.0),\n",
       "  'Token[101]: \"my\"'/'I-ADR' (1.0),\n",
       "  'Token[102]: \"hands\"'/'I-ADR' (1.0),\n",
       "  'Token[103]: \",\"'/'O' (1.0),\n",
       "  'Token[104]: \"and\"'/'O' (1.0),\n",
       "  'Token[105]: \"it\"'/'O' (1.0),\n",
       "  'Token[106]: \"isnt\"'/'O' (1.0),\n",
       "  'Token[107]: \"due\"'/'O' (1.0),\n",
       "  'Token[108]: \"to\"'/'O' (1.0),\n",
       "  'Token[109]: \"me\"'/'O' (1.0),\n",
       "  'Token[110]: \"lying\"'/'O' (1.0),\n",
       "  'Token[111]: \"on\"'/'O' (1.0),\n",
       "  'Token[112]: \"my\"'/'O' (1.0),\n",
       "  'Token[113]: \"arms\"'/'O' (1.0),\n",
       "  'Token[114]: \"or\"'/'O' (1.0),\n",
       "  'Token[115]: \"anything\"'/'O' (1.0),\n",
       "  'Token[116]: \",\"'/'O' (1.0),\n",
       "  'Token[117]: \"and\"'/'O' (1.0),\n",
       "  'Token[118]: \"my\"'/'O' (1.0),\n",
       "  'Token[119]: \"lt\"'/'B-ADR' (1.0),\n",
       "  'Token[120]: \"wrist\"'/'I-ADR' (1.0),\n",
       "  'Token[121]: \"joint\"'/'I-ADR' (1.0),\n",
       "  'Token[122]: \",\"'/'O' (1.0),\n",
       "  'Token[123]: \"where\"'/'O' (1.0),\n",
       "  'Token[124]: \"my\"'/'O' (1.0),\n",
       "  'Token[125]: \"thumb\"'/'O' (1.0),\n",
       "  'Token[126]: \"is\"'/'O' (1.0),\n",
       "  'Token[127]: \"attached\"'/'O' (1.0),\n",
       "  'Token[128]: \",\"'/'O' (1.0),\n",
       "  'Token[129]: \"is\"'/'O' (1.0),\n",
       "  'Token[130]: \"dislocating\"'/'B-ADR' (1.0),\n",
       "  'Token[131]: \"or\"'/'O' (1.0),\n",
       "  'Token[132]: \"it\"'/'O' (1.0),\n",
       "  'Token[133]: \"painfully\"'/'O' (1.0),\n",
       "  'Token[134]: \"sticks\"'/'O' (1.0),\n",
       "  'Token[135]: \".\"'/'O' (1.0),\n",
       "  'Token[136]: \"and\"'/'O' (1.0),\n",
       "  'Token[137]: \"i\"'/'O' (1.0),\n",
       "  'Token[138]: \"have\"'/'O' (1.0),\n",
       "  'Token[139]: \"to\"'/'O' (1.0),\n",
       "  'Token[140]: \"painfully\"'/'O' (1.0),\n",
       "  'Token[141]: \"put\"'/'O' (1.0),\n",
       "  'Token[142]: \"it\"'/'O' (1.0),\n",
       "  'Token[143]: \"back\"'/'O' (1.0),\n",
       "  'Token[144]: \"in\"'/'O' (1.0),\n",
       "  'Token[145]: \".\"'/'O' (1.0),\n",
       "  'Token[146]: \"im\"'/'O' (1.0),\n",
       "  'Token[147]: \"going\"'/'O' (1.0),\n",
       "  'Token[148]: \"to\"'/'O' (1.0),\n",
       "  'Token[149]: \"show\"'/'O' (1.0),\n",
       "  'Token[150]: \"this\"'/'O' (1.0),\n",
       "  'Token[151]: \"website\"'/'O' (1.0),\n",
       "  'Token[152]: \"to\"'/'O' (1.0),\n",
       "  'Token[153]: \"my\"'/'O' (1.0),\n",
       "  'Token[154]: \"gp\"'/'O' (1.0),\n",
       "  'Token[155]: \"!\"'/'O' (1.0),\n",
       "  'Token[156]: \".\"'/'O' (1.0)],\n",
       " 'meddra': ['Token[0]: \"wow\"'/'O' (1.0),\n",
       "  'Token[1]: \",\"'/'O' (1.0),\n",
       "  'Token[2]: \"so\"'/'O' (1.0),\n",
       "  'Token[3]: \"im\"'/'O' (1.0),\n",
       "  'Token[4]: \"not\"'/'O' (1.0),\n",
       "  'Token[5]: \"crazy\"'/'O' (1.0),\n",
       "  'Token[6]: \"after\"'/'O' (1.0),\n",
       "  'Token[7]: \"all\"'/'O' (1.0),\n",
       "  'Token[8]: \"!\"'/'O' (1.0),\n",
       "  'Token[9]: \"my\"'/'O' (1.0),\n",
       "  'Token[10]: \"dr\"'/'O' (1.0),\n",
       "  'Token[11]: \"cant\"'/'O' (1.0),\n",
       "  'Token[12]: \"seem\"'/'O' (1.0),\n",
       "  'Token[13]: \"to\"'/'O' (1.0),\n",
       "  'Token[14]: \"find\"'/'O' (1.0),\n",
       "  'Token[15]: \"out\"'/'O' (1.0),\n",
       "  'Token[16]: \"why\"'/'O' (1.0),\n",
       "  'Token[17]: \"my\"'/'O' (1.0),\n",
       "  'Token[18]: \"feet\"'/'B-Foot_pain' (1.0),\n",
       "  'Token[19]: \"hurt\"'/'I-Foot_pain' (1.0),\n",
       "  'Token[20]: \"in\"'/'O' (1.0),\n",
       "  'Token[21]: \"the\"'/'O' (1.0),\n",
       "  'Token[22]: \"morning\"'/'O' (1.0),\n",
       "  'Token[23]: \"and\"'/'O' (1.0),\n",
       "  'Token[24]: \"unexplained\"'/'O' (1.0),\n",
       "  'Token[25]: \"joint\"'/'B-Arthralgia' (1.0),\n",
       "  'Token[26]: \"pain\"'/'I-Arthralgia' (1.0),\n",
       "  'Token[27]: \",\"'/'O' (1.0),\n",
       "  'Token[28]: \"i\"'/'O' (1.0),\n",
       "  'Token[29]: \"get\"'/'O' (1.0),\n",
       "  'Token[30]: \"even\"'/'O' (1.0),\n",
       "  'Token[31]: \"after\"'/'O' (1.0),\n",
       "  'Token[32]: \"just\"'/'O' (1.0),\n",
       "  'Token[33]: \"sitting\"'/'O' (1.0),\n",
       "  'Token[34]: \"for\"'/'O' (1.0),\n",
       "  'Token[35]: \"an\"'/'O' (1.0),\n",
       "  'Token[36]: \"hour\"'/'O' (1.0),\n",
       "  'Token[37]: \"watching\"'/'O' (1.0),\n",
       "  'Token[38]: \"tv\"'/'O' (1.0),\n",
       "  'Token[39]: \"in\"'/'O' (1.0),\n",
       "  'Token[40]: \"the\"'/'O' (1.0),\n",
       "  'Token[41]: \"evening\"'/'O' (1.0),\n",
       "  'Token[42]: \".\"'/'O' (1.0),\n",
       "  'Token[43]: \"man\"'/'O' (1.0),\n",
       "  'Token[44]: \"i\"'/'O' (1.0),\n",
       "  'Token[45]: \"get\"'/'O' (1.0),\n",
       "  'Token[46]: \"up\"'/'O' (1.0),\n",
       "  'Token[47]: \"and\"'/'O' (1.0),\n",
       "  'Token[48]: \"i\"'/'O' (1.0),\n",
       "  'Token[49]: \"can\"'/'B-Walking_disability' (1.0),\n",
       "  'Token[50]: \"hardly\"'/'I-Walking_disability' (1.0),\n",
       "  'Token[51]: \"walk\"'/'I-Walking_disability' (1.0),\n",
       "  'Token[52]: \".\"'/'O' (1.0),\n",
       "  'Token[53]: \"stiffness\"'/'B-Stiff_legs' (1.0),\n",
       "  'Token[54]: \"in\"'/'I-Stiff_legs' (1.0),\n",
       "  'Token[55]: \"my\"'/'I-Stiff_legs' (1.0),\n",
       "  'Token[56]: \"feet\"'/'I-Stiff_legs' (1.0),\n",
       "  'Token[57]: \",\"'/'O' (1.0),\n",
       "  'Token[58]: \"and\"'/'O' (1.0),\n",
       "  'Token[59]: \"leg\"'/'I-Stiff_legs' (1.0),\n",
       "  'Token[60]: \"joint\"'/'I-Stiff_legs' (1.0),\n",
       "  'Token[61]: \".\"'/'O' (1.0),\n",
       "  'Token[62]: \"dr\"'/'O' (1.0),\n",
       "  'Token[63]: \"has\"'/'O' (1.0),\n",
       "  'Token[64]: \"done\"'/'O' (1.0),\n",
       "  'Token[65]: \"x\"'/'O' (1.0),\n",
       "  'Token[66]: \"-\"'/'O' (1.0),\n",
       "  'Token[67]: \"ray\"'/'O' (1.0),\n",
       "  'Token[68]: \"and\"'/'O' (1.0),\n",
       "  'Token[69]: \"everything\"'/'O' (1.0),\n",
       "  'Token[70]: \".\"'/'O' (1.0),\n",
       "  'Token[71]: \"im\"'/'O' (1.0),\n",
       "  'Token[72]: \"think\"'/'O' (1.0),\n",
       "  'Token[73]: \"he\"'/'O' (1.0),\n",
       "  'Token[74]: \"is\"'/'O' (1.0),\n",
       "  'Token[75]: \"thinking\"'/'O' (1.0),\n",
       "  'Token[76]: \"it\"'/'O' (1.0),\n",
       "  'Token[77]: \"is\"'/'O' (1.0),\n",
       "  'Token[78]: \"in\"'/'O' (1.0),\n",
       "  'Token[79]: \"my\"'/'O' (1.0),\n",
       "  'Token[80]: \"head\"'/'O' (1.0),\n",
       "  'Token[81]: \"all\"'/'O' (1.0),\n",
       "  'Token[82]: \"this\"'/'O' (1.0),\n",
       "  'Token[83]: \"pain\"'/'B-Pain' (1.0),\n",
       "  'Token[84]: \".\"'/'O' (1.0),\n",
       "  'Token[85]: \"now\"'/'O' (1.0),\n",
       "  'Token[86]: \"when\"'/'O' (1.0),\n",
       "  'Token[87]: \"i\"'/'O' (1.0),\n",
       "  'Token[88]: \"so\"'/'O' (1.0),\n",
       "  'Token[89]: \"called\"'/'O' (1.0),\n",
       "  'Token[90]: \"sleep\"'/'O' (1.0),\n",
       "  'Token[91]: \"at\"'/'O' (1.0),\n",
       "  'Token[92]: \"night\"'/'O' (1.0),\n",
       "  'Token[93]: \"i\"'/'O' (1.0),\n",
       "  'Token[94]: \"have\"'/'O' (1.0),\n",
       "  'Token[95]: \"been\"'/'O' (1.0),\n",
       "  'Token[96]: \"noticing\"'/'O' (1.0),\n",
       "  'Token[97]: \"i\"'/'O' (1.0),\n",
       "  'Token[98]: \"get\"'/'O' (1.0),\n",
       "  'Token[99]: \"numbness\"'/'B-Numbness_of_hand' (1.0),\n",
       "  'Token[100]: \"in\"'/'I-Numbness_of_hand' (1.0),\n",
       "  'Token[101]: \"my\"'/'I-Numbness_of_hand' (1.0),\n",
       "  'Token[102]: \"hands\"'/'I-Numbness_of_hand' (1.0),\n",
       "  'Token[103]: \",\"'/'O' (1.0),\n",
       "  'Token[104]: \"and\"'/'O' (1.0),\n",
       "  'Token[105]: \"it\"'/'O' (1.0),\n",
       "  'Token[106]: \"isnt\"'/'O' (1.0),\n",
       "  'Token[107]: \"due\"'/'O' (1.0),\n",
       "  'Token[108]: \"to\"'/'O' (1.0),\n",
       "  'Token[109]: \"me\"'/'O' (1.0),\n",
       "  'Token[110]: \"lying\"'/'O' (1.0),\n",
       "  'Token[111]: \"on\"'/'O' (1.0),\n",
       "  'Token[112]: \"my\"'/'O' (1.0),\n",
       "  'Token[113]: \"arms\"'/'O' (1.0),\n",
       "  'Token[114]: \"or\"'/'O' (1.0),\n",
       "  'Token[115]: \"anything\"'/'O' (1.0),\n",
       "  'Token[116]: \",\"'/'O' (1.0),\n",
       "  'Token[117]: \"and\"'/'O' (1.0),\n",
       "  'Token[118]: \"my\"'/'O' (1.0),\n",
       "  'Token[119]: \"lt\"'/'B-CONCEPT_LESS' (1.0),\n",
       "  'Token[120]: \"wrist\"'/'I-CONCEPT_LESS' (1.0),\n",
       "  'Token[121]: \"joint\"'/'I-CONCEPT_LESS' (1.0),\n",
       "  'Token[122]: \",\"'/'O' (1.0),\n",
       "  'Token[123]: \"where\"'/'O' (1.0),\n",
       "  'Token[124]: \"my\"'/'O' (1.0),\n",
       "  'Token[125]: \"thumb\"'/'O' (1.0),\n",
       "  'Token[126]: \"is\"'/'O' (1.0),\n",
       "  'Token[127]: \"attached\"'/'O' (1.0),\n",
       "  'Token[128]: \",\"'/'O' (1.0),\n",
       "  'Token[129]: \"is\"'/'O' (1.0),\n",
       "  'Token[130]: \"dislocating\"'/'B-Dislocation_of_joint' (1.0),\n",
       "  'Token[131]: \"or\"'/'O' (1.0),\n",
       "  'Token[132]: \"it\"'/'O' (1.0),\n",
       "  'Token[133]: \"painfully\"'/'O' (1.0),\n",
       "  'Token[134]: \"sticks\"'/'O' (1.0),\n",
       "  'Token[135]: \".\"'/'O' (1.0),\n",
       "  'Token[136]: \"and\"'/'O' (1.0),\n",
       "  'Token[137]: \"i\"'/'O' (1.0),\n",
       "  'Token[138]: \"have\"'/'O' (1.0),\n",
       "  'Token[139]: \"to\"'/'O' (1.0),\n",
       "  'Token[140]: \"painfully\"'/'O' (1.0),\n",
       "  'Token[141]: \"put\"'/'O' (1.0),\n",
       "  'Token[142]: \"it\"'/'O' (1.0),\n",
       "  'Token[143]: \"back\"'/'O' (1.0),\n",
       "  'Token[144]: \"in\"'/'O' (1.0),\n",
       "  'Token[145]: \".\"'/'O' (1.0),\n",
       "  'Token[146]: \"im\"'/'O' (1.0),\n",
       "  'Token[147]: \"going\"'/'O' (1.0),\n",
       "  'Token[148]: \"to\"'/'O' (1.0),\n",
       "  'Token[149]: \"show\"'/'O' (1.0),\n",
       "  'Token[150]: \"this\"'/'O' (1.0),\n",
       "  'Token[151]: \"website\"'/'O' (1.0),\n",
       "  'Token[152]: \"to\"'/'O' (1.0),\n",
       "  'Token[153]: \"my\"'/'O' (1.0),\n",
       "  'Token[154]: \"gp\"'/'O' (1.0),\n",
       "  'Token[155]: \"!\"'/'O' (1.0),\n",
       "  'Token[156]: \".\"'/'O' (1.0)]}"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.annotation_layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# # import seaborn as sns\n",
    "# import matplotlib.pyplot as plt\n",
    "# from collections import Counter\n",
    "# from itertools import chain\n",
    "# # from flair.data import Sentence\n",
    "\n",
    "# Assume that you have a list of Flair Sentence objects called 'sentences'\n",
    "text = ' '.join([str(sentence) for sentence in docs])\n",
    "words = text.split()\n",
    "word_freq = Counter(words)\n",
    "sorted_word_freq = sorted(word_freq.items(), key=lambda x: x[1], reverse=True)\n",
    "freqs = [f for w, f in sorted_word_freq]\n",
    "ranks = range(1, len(sorted_word_freq)+1)\n",
    "\n",
    "# Set the plot style and scale\n",
    "sns.set_style(\"whitegrid\")\n",
    "sns.set_context(\"paper\", font_scale=1.5)\n",
    "sns.set_palette(\"Set1\", 8, .75)\n",
    "sns.set(rc={'figure.figsize':(10,10)})\n",
    "sns.color_palette(\"tab10\")\n",
    "\n",
    "# Create the plot\n",
    "sns.lineplot(x=ranks, y=freqs)\n",
    "plt.xscale('log')\n",
    "plt.yscale('log')\n",
    "plt.xlabel('Word rank (log scale)')\n",
    "plt.ylabel('Word frequency (log scale)')\n",
    "plt.title('Word Frequency Distribution')\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_all_labels(token):\n",
    "    res = dict()\n",
    "    for typename in token.sentence.annotation_layers.keys():\n",
    "        res[typename] = [a for a in token.sentence.annotation_layers[typename] if a.data_point.start_position == token.start_position]\n",
    "    return res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_docs, test_docs = train_test_split(docs, test_size=0.2, random_state=321)\n",
    "dev_docs, test_docs = train_test_split(test_docs, test_size=0.5, random_state=123)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unique NER tags: Counter({'I-ADR': 7953, 'B-ADR': 4712, 'B-Drug': 1396, 'I-Finding': 349, 'B-Finding': 309, 'B-Disease': 231, 'B-Symptom': 222, 'I-Symptom': 218, 'I-Disease': 169, 'I-Drug': 161})\n",
      "Unique Meddra tags: Counter({'B-Lipitor': 825, 'I-CONCEPT_LESS': 746, 'I-Severe_pain': 425, 'B-CONCEPT_LESS': 351, 'I-Myalgia': 296, 'B-Pain': 290, 'B-Myalgia': 210, 'I-Muscle_weakness': 152, 'B-Severe_pain': 138, 'I-Arthralgia': 137, 'I-Walking_disability': 127, 'I-Cramp_in_lower_limb': 115, 'I-Pain_in_lower_limb': 115, 'I-Hip_pain': 114, 'B-Fatigue': 112, 'B-Arthralgia': 109, 'B-Muscle_cramp': 104, 'I-Shoulder_pain': 103, 'I-Pins_and_needles': 103, 'I-Foot_pain': 102, 'I-Backache': 101, 'I-Weakness_of_limb': 101, 'B-Depression': 98, 'I-Knee_pain': 94, 'I-Poor_short-term_memory': 93, 'B-Excessive_upper_gastrointestinal_gas': 92, 'B-Headache': 88, 'I-Excessive_upper_gastrointestinal_gas': 86, 'I-Neck_pain': 85, 'B-Asthenia': 76, 'I-Generalised_aches_and_pains': 75, 'I-Muscle_atrophy': 74, 'I-Stomach_ache': 73, 'I-Mentally_dull': 73, 'I-Muscle_cramp': 70, 'B-Cramp_in_lower_limb': 67, 'B-Backache': 66, 'I-Low_back_pain': 65, 'I-Amnesia': 62, 'I-Influenza-like_illness': 61, 'B-Diarrhoea': 60, 'B-Muscle_weakness': 59, 'B-Amnesia': 58, 'B-Pain_in_lower_limb': 58, 'I-Unable_to_walk': 57, 'B-Hip_pain': 56, 'I-Pain_in_calf': 56, 'B-Dizziness': 53, 'B-Walking_disability': 53, 'I-Myalgia/myositis_-_lower_leg': 53, 'I-Unable_to_get_off_a_bed': 52, 'B-Nausea': 51, 'B-Knee_pain': 50, 'I-Rash': 49, 'B-Shoulder_pain': 49, 'I-Memory_impairment': 48, 'B-Insomnia': 48, 'I-Lightheadedness': 48, 'B-Stomach_ache': 47, 'B-Pins_and_needles': 47, 'I-Pain_in_upper_limb': 46, 'B-Arthrotec': 45, 'I-Flushing': 44, 'I-Headache': 43, 'B-Arthritis': 43, 'B-Foot_pain': 43, 'I-Charleyhorse': 43, 'B-Neck_pain': 42, 'I-Muscle_fatigue': 42, 'I-Numbness_of_lower_limb': 42, 'I-Asthenia': 41, 'I-Reduced_libido': 41, 'I-Loss_of_hair': 41, 'I-Difficulty_sleeping': 39, 'I-Visual_disturbance': 38, 'I-Myocardial_infarction': 38, 'I-Blurred_vision_-_hazy': 38, 'I-Loss_of_motivation': 37, 'I-Unable_to_concentrate': 37, 'I-Pain_provoked_by_movement': 37, 'B-Zocor': 37, 'I-Stomach_cramps': 36, 'B-Myocardial_infarction': 36, 'I-Thigh_pain': 36, 'I-Fatigue': 34, 'I-Ankle_pain': 34, 'I-Tired': 34, 'B-Loss_of_hair': 34, 'I-Myopathy': 34, 'I-Upset_stomach': 33, 'B-Weakness_of_limb': 33, 'B-ubidecarenone': 32, 'I-Myalgia/myositis_-_shoulder': 32, 'B-Bloating_symptom': 31, 'B-Tired': 31, 'I-Lack_of_energy': 31, 'I-Cramp_in_calf': 30, 'I-Impairment_of_balance': 30, 'I-Cannot_sleep_at_all': 30, 'I-Acid_reflux': 30, 'I-Dyspnoea': 30, 'B-Blurred_vision_-_hazy': 29, 'I-Chest_pain': 29, 'I-Pain': 29, 'B-Mentally_dull': 28, 'B-Muscle_atrophy': 28, 'I-Burning_feet': 28, 'I-Bleeding_between_periods': 28, 'I-Restless_legs': 27, 'B-Generalised_aches_and_pains': 27, 'I-Weight_gain': 27, 'B-Poor_short-term_memory': 27, 'I-Tired_all_the_time': 27, 'I-Abdominal_pain': 27, 'I-Difficulty_walking_up_stairs': 26, 'B-Rash': 26, 'I-Muscle_twitch': 26, 'I-Serum_cholesterol_raised': 26, 'I-Unable_to_climb_stairs': 26, 'B-Low_back_pain': 26, 'I-Sensation_of_hot_and_cold': 26, 'I-Generalised_acute_body_pains': 26, 'B-Constipation': 25, 'B-Anxiety': 25, 'I-Unable_to_think_clearly': 24, 'B-Memory_impairment': 24, 'I-Cramp_in_foot': 24, 'B-Vertigo': 24, 'B-Chest_pain': 24, 'I-Thoracic_back_pain': 24, 'I-Paraesthesia_of_lower_extremity': 24, 'B-Stomach_cramps': 23, 'B-Voltaren': 23, 'I-Finding_of_increased_blood_pressure': 23, 'I-Unable_to_walk_up_step': 23, 'B-Pravachol': 22, 'I-Liver_enzymes_abnormal': 22, 'B-Myopathy': 22, 'I-Rupture_of_Achilles_tendon': 22, 'I-Myalgia/myositis_-pelvis/thigh': 22, 'I-Stiff_legs': 22, 'I-Burning_pain': 22, 'I-Hypersomnia': 21, 'I-Pulse_fast': 21, 'B-Unable_to_walk': 21, 'B-Influenza-like_illness': 21, 'B-Numbness': 21, 'I-Unable_to_move_arm': 21, 'I-Myalgia/myositis_-_multiple': 21, 'B-Difficulty_sleeping': 20, 'B-Upset_stomach': 20, 'I-Burning_sensation': 20, 'I-Heart_disease': 20, 'B-Lightheadedness': 20, 'B-Cannot_sleep_at_all': 20, 'B-Flatulence/wind': 20, 'B-Bleeding': 20, 'B-Abdominal_pain': 20, 'I-Tight_chest': 20, 'I-Myalgia/myositis_-_forearm': 20, 'B-Itching': 20, 'I-Postmenopausal_bleeding': 20, 'I-Stabbing_pain': 20, 'I-Arthritis_of_hand': 20, 'B-Visual_disturbance': 19, 'I-Plantar_fasciitis': 19, 'B-Pain_in_calf': 19, 'B-Weight_gain': 19, 'I-Generally_unwell': 19, 'I-Hand_pain': 19, 'I-Muscle_tension': 19, 'I-Uterine_spasm': 19, 'I-Pain_in_elbow': 19, 'I-Spasm_of_back_muscles': 19, 'B-Increased_cholesterol_esters': 18, 'I-Increased_cholesterol_esters': 18, 'B-Heart_disease': 18, 'B-Feeling_irritable': 18, 'B-Lack_of_energy': 18, 'B-Stiffness': 18, 'I-Constant_pain': 18, 'I-Pain_provoked_by_walking': 18, 'I-Limitation_of_joint_movement': 18, 'I-Random_blood_sugar_raised': 18, 'I-Tachycardia': 17, 'I-Intercostal_myalgia': 17, 'I-Liver_disease': 17, 'I-Irregular_menstruation': 17, 'B-Reduced_libido': 17, 'I-Failure_to_lose_weight': 17, 'I-Itching_of_skin': 17, 'B-Pain_in_upper_limb': 17, 'I-Paraesthesia_of_hand': 17, 'I-Unable_to_balance': 17, 'I-Tinnitus': 17, 'B-Muscle_fatigue': 16, 'B-Unable_to_concentrate': 16, 'B-Burning_sensation': 16, 'B-Swelling': 16, 'I-Menorrhagia': 16, 'I-Vaginal_bleeding': 16, 'I-Increased_venous_pressure': 16, 'B-Crestor': 16, 'I-Excruciating_pain': 16, 'B-Dyspnoea': 16, 'I-Difficulty_getting_off_a_bed': 16, 'I-Impaired_exercise_tolerance': 16, 'I-Peripheral_neuropathy': 16, 'B-Tiredness_symptom': 16, 'I-Numbness_of_limbs': 15, 'I-Abdominal_colic': 15, 'I-Serum_creatinine_raised': 15, 'I-Heel_pain': 15, 'B-Exhaustion': 15, 'B-Myalgia/myositis_-_lower_leg': 15, 'I-omega-3-acid_ethyl_esters-90': 15, 'I-Foot_swelling': 15, 'I-Loss_of_taste': 15, 'I-Numbness_of_hand': 15, 'I-Acute_pain': 15, 'I-Urinary_frequency': 15, 'I-Mood_swings': 14, 'I-Incoordination': 14, 'B-Impairment_of_balance': 14, 'B-Ankle_pain': 14, 'B-Diabetes_mellitus': 14, 'B-ascorbic_acid': 14, 'I-ascorbic_acid': 14, 'B-Fibromyalgia': 14, 'B-Vaginal_bleeding': 14, 'I-Numbness_of_upper_limb': 14, 'I-Heavy_legs': 14, 'I-Sharp_pain': 14, 'I-Haematochezia': 14, 'I-Arthralgia_of_the_lower_leg': 14, 'I-Pain_in_toe': 14, 'I-Weakness_of_hand': 14, 'B-ezetimibe': 13, 'B-Loss_of_motivation': 13, 'I-Dizziness': 13, 'I-Tightness_in_throat': 13, 'I-Aptyalism': 13, 'I-Migraine': 13, \"I-Bell's_palsy\": 13, 'I-Lack_of_stamina': 13, 'I-Sensation_of_heaviness_in_limbs': 13, 'I-Poor_concentration': 13, 'I-Facial_swelling': 13, 'B-Tinnitus': 13, 'I-Elbow_joint_pain': 13, 'I-Malaise': 13, 'I-Irritable_bowel_syndrome_characterised_by_constipation': 13, 'I-Pain_in_left_arm': 13, 'I-Deep_pain': 13, 'I-Aphasia': 13, 'I-Spasm': 12, 'B-Tendonitis': 12, 'B-Cramp_in_calf': 12, 'B-ibuprofen': 12, 'B-Muscle_twitch': 12, 'B-Liver_disease': 12, 'B-Amyotrophic_lateral_sclerosis': 12, 'I-Derealisation': 12, 'I-Myalgia/myositis_-_upper_arm': 12, 'I-ubidecarenone': 12, 'B-Acid_reflux': 12, 'I-Joint_stiffness': 12, 'B-Pain_in_elbow': 12, 'I-Personality_change': 12, 'I-Ringing_in_ear': 12, 'I-Difficulty_breathing': 12, 'I-Hand_joint_stiff': 12, 'B-Vomiting': 12, 'B-Spasm': 11, 'B-Drowsy': 11, 'B-Mood_swings': 11, 'I-Dry_skin': 11, 'B-Restless_legs': 11, 'B-Thigh_pain': 11, 'I-Body_fluid_retention': 11, 'B-Migraine': 11, 'I-Bleeding': 11, 'I-Discolouration_of_skin': 11, 'I-Vertigo': 11, 'B-Tired_all_the_time': 11, 'B-Palpitations': 11, 'B-Tremor': 11, 'B-fenofibrate': 11, 'B-Indigestion': 11, 'I-Hypertension': 11, 'B-Confusion': 11, 'I-Knee_stiff': 11, 'I-Difficulty_chewing': 11, 'I-Weight_increased': 11, 'B-Cerebrovascular_accident': 11, 'I-Flatulence,_eructation_and_gas_pain': 11, 'B-Charleyhorse': 11, 'I-Cramp_in_lower_leg': 11, 'I-Calf_muscle_weakness': 11, 'B-Unable_to_think_clearly': 10, 'I-Numbness_of_foot': 10, 'B-Abdominal_colic': 10, 'I-Cramp_in_limb': 10, 'B-Moody': 10, 'I-Feeling_empty': 10, 'B-Serum_creatinine_raised': 10, 'I-Flatulence/wind': 10, 'I-Lack_of_libido': 10, 'B-Aptyalism': 10, 'B-Finding_of_increased_blood_pressure': 10, 'I-Spasmodic_movement': 10, 'I-Loss_of_appetite': 10, 'I-fish_oil_natural': 10, 'I-Swollen_legs': 10, 'B-Neuropathy': 10, 'I-Nerve_injury': 10, 'I-Haemorrhage_of_abdominal_cavity_structure': 10, 'B-Malaise': 10, 'I-Pain_in_left_leg': 10, 'I-Lower_abdominal_pain': 10, 'I-Paraesthesia_of_foot': 10, 'I-Loss_of_interest': 10, 'I-Swollen_ankle': 10, 'I-Clicking_interphalangeal_joint_of_toe': 10, 'I-Initial_insomnia': 10, 'I-Malignant_neoplasm_of_brain': 10, 'I-Reduced_mobility': 9, 'I-Swelling_of_finger': 9, 'I-Peeling_of_skin': 9, 'I-Oedema_of_lower_extremity': 9, 'B-Cough': 9, 'B-Cramp_in_foot': 9, 'B-Influenza': 9, 'B-Hypertension': 9, 'B-Gout': 9, 'B-Hand_pain': 9, 'B-Inflammatory_disorder': 9, 'B-Constant_pain': 9, 'B-Serum_cholesterol_raised': 9, 'I-Unable_to_stand': 9, 'I-Weight_loss': 9, 'I-Depression': 9, 'I-Renal_impairment': 9, 'I-White_blood_cell_count_abnormal': 9, 'I-Acenaesthesia': 9, 'I-Shoulder_joint_pain': 9, 'I-Pain_in_finger': 9, 'I-Stiffness': 9, 'B-Peripheral_neuropathy': 9, 'I-Unsteady_when_standing': 9, 'I-Menstrual_cramp': 9, 'I-Heavy_feeling': 9, 'B-Multiple_sclerosis': 9, 'I-Numbness_of_face': 9, 'I-Ovarian_pain': 9, 'B-Celebrex': 9, 'I-Oedema_of_extremity': 9, 'I-Increased_liver_function': 9, 'B-Tachycardia': 8, 'I-Erythema_of_skin': 8, 'B-Unable_to_get_off_a_bed': 8, 'B-Hypersomnia': 8, 'B-Plantar_fasciitis': 8, 'I-alpha_tocopherol': 8, 'I-Tylenol': 8, 'I-Hand_cramps': 8, 'B-Stiff_neck': 8, 'I-Stiff_neck': 8, 'B-Spasmodic_movement': 8, 'I-Kidney_disease': 8, 'I-Muscle_rigidity': 8, 'I-Renal_pain': 8, 'B-Severe_depression': 8, 'I-Severe_depression': 8, 'I-Suicidal_thoughts': 8, 'B-Advil': 8, 'B-Rheumatoid_arthritis': 8, 'B-Lupus_erythematosus': 8, 'B-Liver_enzymes_abnormal': 8, 'B-Heel_pain': 8, 'B-Poor_concentration': 8, 'I-Dry_eyes': 8, 'B-simvastatin': 8, 'B-omega-3-acid_ethyl_esters-90': 8, 'B-Joint_stiffness': 8, 'B-Increased_venous_pressure': 8, 'B-Aleve': 8, 'B-Heartburn': 8, 'B-Excruciating_pain': 8, 'B-Limping': 8, 'I-Limping': 8, 'B-Stress': 8, 'I-Feeling_faint': 8, 'B-diclofenac': 8, 'B-Difficulty_breathing': 8, 'B-Pain_in_toe': 8, 'I-Type_2_diabetes_mellitus': 8, 'B-Menstrual_cramp': 8, 'I-Right_hemiparesis': 8, 'B-Flushing': 8, 'I-Unable_to_find_words': 8, 'I-Unable_to_lift': 8, 'I-Tendonitis_AND/OR_tenosynovitis_of_the_elbow_region': 8, 'I-Large_breast': 8, 'I-Clicking_knee': 8, 'I-Symptom_of_ankle': 8, 'I-Increased_lactic_acid_level': 8, 'I-Tremor': 8, 'I-Parkinsonian_tremor': 8, 'I-Abdominal_hyperaesthesia': 8, 'I-Tenalgia': 8, 'I-Unable_to_move_leg': 7, 'B-Tylenol': 7, 'B-Burning_feet': 7, 'B-Kidney_disease': 7, 'B-Myalgia/myositis_-_shoulder': 7, 'B-Forgetful': 7, 'I-Non-smoker': 7, 'B-Generally_unwell': 7, 'I-Rheumatoid_arthritis': 7, 'I-Muscle_strain': 7, 'B-Pain_provoked_by_movement': 7, 'B-Itching_of_skin': 7, 'I-Unsteady_when_walking': 7, 'B-Lack_of_stamina': 7, 'B-Loss_of_appetite': 7, 'I-Serum_triglycerides_raised': 7, 'B-fish_oil_natural': 7, 'B-Paraesthesia_of_hand': 7, 'I-Urinary_retention': 7, 'I-Palpitations': 7, \"I-Parkinson's_disease\": 7, 'I-Difficulty_lifting': 7, 'I-Gastrointestinal_tract_problem': 7, 'B-Impaired_exercise_tolerance': 7, 'B-Delusional_disorder': 7, 'I-Nausea': 7, 'B-Lethargy': 7, 'I-Insomnia': 7, 'B-Menopause_present': 7, 'I-Itching': 7, 'B-Random_blood_sugar_raised': 7, 'I-Unable_to_get_out_of_a_chair': 7, 'I-Confusion': 7, 'I-Slurred_speech': 7, 'I-Numbness': 7, 'B-Illness': 7, 'B-Unable_to_balance': 7, 'I-Panic_attack': 7, 'I-Stomach_problem': 7, 'I-Dysphonia': 7, 'I-Shoulder_stiff': 7, 'I-Intervertebral_disc_prolapse': 7, 'I-Joint_crepitus': 7, 'I-Urine:_dark/concentrated': 7, 'I-Blistering_rash': 7, 'B-Swollen_ankle': 7, 'I-Tingling_of_skin': 7, 'I-Unable_to_lie_down': 7, 'I-Numbness_and_tingling_sensation_of_skin': 7, 'I-Discomfort': 7, 'I-Coronary_arteriosclerosis': 7, 'I-Hand_joint_pain': 7, 'I-Tightness_sensation': 7, 'B-Pulse_fast': 6, 'B-Sweating': 6, 'I-Glossitis': 6, 'I-Stiff_limbs': 6, 'I-cortisone': 6, 'I-Difficulty_swallowing': 6, 'I-Carpal_tunnel_syndrome': 6, 'I-Arthritis': 6, 'I-Myositis': 6, 'B-Muscle_rigidity': 6, 'B-Menorrhagia': 6, 'I-Infective_cystitis': 6, 'B-Lopid': 6, 'I-Exhaustion': 6, 'B-Unable_to_climb_stairs': 6, 'B-Weight_loss': 6, 'I-Rib_pain': 6, 'B-Uterine_spasm': 6, 'I-Cold_sweat': 6, 'B-prednisone': 6, 'I-Swelling_of_knee_joint': 6, 'I-Swollen_knee': 6, 'B-Disorientated': 6, 'B-Asthma': 6, 'I-Sleep_deprivation': 6, 'B-Zoloft': 6, 'B-Spasm_of_back_muscles': 6, 'B-Nerve_injury': 6, 'I-C-reactive_protein_abnormal': 6, 'I-Excessive_and_frequent_menstruation': 6, 'I-Increased_creatine_kinase_level': 6, 'B-Slurred_speech': 6, 'I-Reduction_of_bulk_of_muscle': 6, 'I-Respiratory_depression': 6, 'B-Panic_attack': 6, 'B-Stomach_problem': 6, 'B-Paraesthesia_of_lower_extremity': 6, 'B-ezetimibe_+_simvastatin': 6, 'I-Pain_in_wrist': 6, 'I-Abdominal_wind_pain': 6, 'B-Fever': 6, 'B-Numbness_of_hand': 6, 'I-Hypertonia': 6, 'I-Decreased_cholesterol_esters': 6, 'I-Impaired_mobility': 6, 'I-Heartburn': 6, 'B-Numbness_of_lower_limb': 6, 'I-Dependance_on_walking_stick': 6, 'I-Difficulty_moving_hand': 6, 'I-Mucosal_numbness': 6, 'I-Acne': 6, 'I-Bizarre_dreams': 6, 'I-Achilles_tendonitis': 6, 'I-Night_pain': 6, 'I-Heavy_episode_of_vaginal_bleeding': 6, 'I-Diarrhoea': 6, 'I-Difficulty_getting_out_of_a_chair': 6, 'I-Blind_or_low_vision_-_one_eye_only': 6, 'I-Always_sleepy': 6, 'I-Hyperaemia_of_surface_of_eye': 6, 'I-Pain_provoked_by_rest': 6, 'I-Difficulty_standing': 6, 'I-Abdominal_bloating': 5, 'B-Dry_skin': 5, 'B-Numbness_of_foot': 5, 'B-cortisone': 5, 'B-alpha_tocopherol': 5, 'B-Difficulty_swallowing': 5, 'I-Chronic_back_pain': 5, 'I-Disorder_of_foot': 5, 'B-Malignant_neoplastic_disease': 5, 'B-Tightness_in_throat': 5, 'B-Renal_pain': 5, 'B-Syncope': 5, 'I-Forgetful': 5, 'I-Urinary_tract_infection': 5, 'I-Bone_pain': 5, 'I-Digestive_symptom': 5, 'I-Scalp_itchy': 5, \"B-Bell's_palsy\": 5, 'I-Abnormal_dreams': 5, 'I-Swallowing_problem': 5, 'B-Muscle_tension': 5, 'B-Feeling_unhappy': 5, 'B-Dry_eyes': 5, 'I-Arthrotec': 5, 'I-Photosensitisation_due_to_sun': 5, 'B-Pain_provoked_by_walking': 5, 'B-Facial_swelling': 5, 'I-Excessive_sweating': 5, 'I-Hoarse': 5, 'B-Rib_pain': 5, 'I-Pounding_heart': 5, 'B-Chill': 5, 'B-Foot_swelling': 5, 'B-Tight_chest': 5, 'B-Thoracic_back_pain': 5, 'B-Limitation_of_joint_movement': 5, 'B-Myalgia/myositis_-_forearm': 5, 'I-Lumbar_facet_joint_pain': 5, 'I-Fear': 5, 'B-Heavy_legs': 5, 'B-Myalgia/myositis_-pelvis/thigh': 5, 'B-Nasal_sinus_problem': 5, 'I-Nasal_sinus_problem': 5, 'B-Stiff_legs': 5, 'B-Loss_of_taste': 5, 'I-Urine_looks_dark': 5, 'B-Pain_in_finger': 5, 'B-Knee_stiff': 5, 'I-Hip_stiff': 5, 'B-Discomfort': 5, 'I-Slow_on_legs': 5, 'B-Pain_in_throat': 5, 'I-Pain_in_throat': 5, 'I-Unable_to_eat': 5, 'B-Pain_in_wrist': 5, 'B-Weight_increased': 5, 'I-Bipolar_disorder': 5, 'I-Low_blood_pressure_reading': 5, 'I-Gastric_ulcer': 5, 'I-Fine_motor_impairment': 5, 'I-Lateral_epicondylitis': 5, 'I-Arthritis_of_knee': 5, 'I-Arthritis_of_hip': 5, 'B-Stabbing_pain': 5, 'B-Type_2_diabetes_mellitus': 5, 'I-Chronic_fatigue_syndrome': 5, 'I-Middle_insomnia': 5, 'I-Swollen_nasal_mucosa': 5, 'I-Yellow_skin': 5, 'B-Cramp_in_lower_leg': 5, 'I-Arthralgia_of_multiple_joints': 5, 'I-Wrist_joint_pain': 5, 'B-Bizarre_dreams': 5, 'I-Shoulder_tendonitis': 5, 'I-Pancreatitis': 5, 'I-Rupture_of_tendon_of_lower_leg_and_ankle': 5, 'I-Hyperaesthesia': 5, 'I-Impaired_bed_mobility': 5, 'I-Musculoskeletal_pain': 5, 'B-Norvasc': 5, 'I-Unable_to_speak': 5, 'I-Unable_to_move_all_four_limbs': 5, 'I-Strain_of_calf_muscle': 5, 'I-Difficulty_dressing': 5, 'I-Feels_everything_is_futile': 5, 'B-Reduced_mobility': 4, 'B-Difficulty_walking_up_stairs': 4, 'B-Abdominal_bloating': 4, 'B-Eczema': 4, 'B-Swelling_of_finger': 4, 'I-Propensity_to_adverse_reactions_to_drug': 4, 'I-Unable_to_walk_down_stairs': 4, 'B-Hand_cramps': 4, 'B-Carpal_tunnel_syndrome': 4, 'B-aspirin': 4, 'B-Rhabdomyolysis': 4, 'B-Infective_cystitis': 4, 'B-Lack_of_libido': 4, 'B-Nightmares': 4, 'I-Hepatic_trauma': 4, 'B-Diovan': 4, 'B-Haematuria': 4, 'B-Suicidal_thoughts': 4, 'B-Muscle_strain': 4, 'I-Type_1_diabetes_mellitus': 4, 'B-Steatosis_of_liver': 4, 'I-Steatosis_of_liver': 4, 'B-Disorder_of_muscle': 4, 'B-Sensation_of_heaviness_in_limbs': 4, 'B-Abnormal_dreams': 4, 'B-Swallowing_problem': 4, 'I-Right_upper_quadrant_pain': 4, 'I-Liver_function_tests_abnormal': 4, 'I-Gallbladder_disorder': 4, 'I-Rupture_of_tendon': 4, 'B-Photosensitisation_due_to_sun': 4, 'I-Deteriorating_renal_function': 4, 'I-Pain_in_thumb': 4, 'I-Burning_sensation_of_vagina': 4, 'B-Excessive_sweating': 4, 'B-Cramp': 4, 'I-Cramp': 4, 'B-Swollen_legs': 4, \"B-Parkinson's_disease\": 4, 'I-Neuroma_of_foot': 4, 'B-Swollen_knee': 4, 'I-Neuropathy_of_upper_limb': 4, 'I-Swelling_of_hand': 4, 'B-Numbness_of_upper_limb': 4, 'I-Ankle_oedema': 4, 'I-Urinary_incontinence': 4, 'B-Sciatica': 4, 'I-Disorder_of_nasal_sinus': 4, 'I-Pain_in_limb': 4, 'B-Elbow_joint_pain': 4, 'B-Ringing_in_ear': 4, 'B-Increased_creatine_kinase_level': 4, 'I-Tendonitis': 4, 'B-Bronchitis': 4, 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'I-Irregular_heart_beat': 4, 'I-Muscle_injury': 4, 'I-Warm_hands': 4, 'I-Compression_neuropathy_of_trunk': 4, 'I-Muscle_fasciculation': 4, 'I-Intolerant_of_cold': 4, 'B-Malignant_neoplasm_of_brain': 4, 'I-Haematuria': 4, 'I-Knee_joint_painful_on_movement': 4, 'B-Acute_pain': 4, 'I-Numbness_of_toe': 4, 'B-paracetamol': 4, 'I-Ankle_joint_pain': 4, 'I-Unable_to_move_hand': 4, 'I-Iliotibial_band_friction_syndrome': 4, 'I-Malaise_and_fatigue': 4, 'I-Diastolic_dysfunction': 4, 'I-Right_ventricular_dilatation': 4, 'I-Abdominal_distension': 4, 'I-Pain_in_cheek': 4, 'I-Skin_nodule': 4, 'B-Loose_stool': 3, 'I-Loose_stool': 3, 'B-Peeling_of_skin': 3, 'B-Incoordination': 3, 'B-Numbness_of_limbs': 3, 'B-Stiff_limbs': 3, 'B-Myositis': 3, 'B-Disorder_of_foot': 3, 'B-Cramp_in_limb': 3, 'I-Moody': 3, 'B-Increased_appetite': 3, 'I-Increased_appetite': 3, 'B-Feeling_empty': 3, 'B-glucosamine': 3, 'B-Irregular_menstruation': 3, 'I-Nonspecific_abdominal_symptom': 3, 'I-Chronic_intractable_pain': 3, 'B-metoprolol': 3, 'B-Body_fluid_retention': 3, 'I-Collapse': 3, 'B-Blister': 3, 'I-Urgent_desire_to_urinate': 3, 'B-Bone_pain': 3, 'B-Digestive_symptom': 3, 'B-Scalp_itchy': 3, 'I-Lip_swelling': 3, 'I-Unable_to_make_a_fist': 3, 'B-Myalgia/myositis_-_upper_arm': 3, 'I-Impairment_level_of_vision': 3, 'B-Serum_triglycerides_raised': 3, 'I-Cardiomyopathy': 3, 'B-Lipex': 3, 'I-Cut_of_hand': 3, 'B-Hoarse': 3, 'I-Lipitor_40_mg_tablet:_film-coated': 3, 'B-misoprostol': 3, 'B-Cold_sweat': 3, 'B-Renal_impairment': 3, 'B-Neurontin': 3, 'I-Bad_taste_in_mouth': 3, 'I-Lopid': 3, 'I-Tendonitis_of_knee': 3, 'B-Swelling_of_knee_joint': 3, 'B-Difficulty_getting_off_a_bed': 3, 'I-Drinks_wine': 3, 'B-Taste_sense_altered': 3, 'I-Taste_sense_altered': 3, 'B-Personality_change': 3, 'B-Sleep_deprivation': 3, 'B-Lipidil': 3, 'I-Menstrual_loss_increasing': 3, 'B-Shoulder_joint_pain': 3, 'B-Sensation_of_hot_and_cold': 3, 'I-Pain_in_spine': 3, 'I-Bursitis_of_hip': 3, 'B-Endometriosis': 3, 'B-Aphasia': 3, 'I-Spots_on_skin': 3, 'I-Visual_impairment': 3, 'I-Sacroiliac_joint_stiff': 3, 'I-Sense_of_smell_impaired': 3, 'B-Renal_failure': 3, 'I-Renal_failure': 3, 'B-Bleeding_between_periods': 3, 'B-Sharp_pain': 3, 'I-Cough': 3, 'B-Disorder_of_eye': 3, 'I-Disorder_of_eye': 3, 'I-paracetamol_+_codeine': 3, 'I-Fear_of_falling': 3, 'I-Clammy_skin': 3, 'B-Hungry': 3, 'I-Loss_of_voice': 3, 'B-Choking': 3, 'I-Tinea_pedis': 3, 'B-Rectal_haemorrhage': 3, 'I-Rectal_haemorrhage': 3, 'B-Colitis': 3, 'B-Burning_pain': 3, 'I-Cold_foot': 3, 'B-Hot_sweats': 3, 'B-Feeling_agitated': 3, 'B-Sinusitis': 3, 'I-Sinusitis': 3, 'I-Respiratory_tract_congestion': 3, 'I-Problem_of_visual_accommodation': 3, 'I-Arthralgia_of_the_upper_arm': 3, 'I-Burning_epigastric_pain': 3, 'I-Constantly_crying': 3, 'B-Bipolar_disorder': 3, 'B-Osteoarthritis': 3, 'I-Rupture_of_muscle': 3, 'B-Low_blood_pressure_reading': 3, 'B-Overweight': 3, 'B-Raised_low_density_lipoprotein_cholesterol': 3, 'I-Raised_low_density_lipoprotein_cholesterol': 3, 'B-potassium': 3, 'B-Always_hungry': 3, 'I-Always_hungry': 3, 'I-Moderate_anxiety': 3, 'B-Lateral_epicondylitis': 3, 'B-Hypertonia': 3, 'B-Infection': 3, 'B-morphine': 3, 'B-Chronic_fatigue_syndrome': 3, 'I-Impaired_cognition': 3, 'I-Buzzing_in_ear': 3, 'I-Infectious_disease_of_lung': 3, 'I-Cervical_arthritis': 3, 'I-Furuncle': 3, 'B-Lower_abdominal_pain': 3, 'B-Irritable_bowel_syndrome': 3, 'B-Numbness_of_face': 3, 'B-Urine:_dark/concentrated': 3, 'I-Disorientated': 3, 'B-Loss_of_interest': 3, 'I-Pressure': 3, 'B-Weakness_of_hand': 3, 'I-Feeling_tired': 3, 'I-Facial_spasm': 3, 'I-Pain_in_pelvis': 3, 'I-Cerebrovascular_accident': 3, 'I-Tightness_in_arm': 3, 'B-Tingling_of_skin': 3, 'I-Elevated_cholesterol/high_density_lipoprotein_ratio': 3, 'I-Disorder_of_face': 3, 'B-Achilles_tendonitis': 3, 'B-Arthritis_of_hand': 3, 'I-Abnormal_gait': 3, 'B-codeine': 3, 'B-Increased_liver_function': 3, 'B-Pancreatitis': 3, 'B-Initial_insomnia': 3, 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'I-Not_getting_enough_sleep': 3, 'I-White_discolouration_of_skin': 3, 'I-Traumatic_blister_of_mouth': 3, 'I-Pain_of_uterus': 3, 'I-Morbid_thoughts': 3, 'B-Erythema_of_skin': 2, 'I-Abnormal_liver_function': 2, 'B-Oedema_of_lower_extremity': 2, 'B-Unable_to_move_leg': 2, 'B-Chronic_back_pain': 2, 'B-Intercostal_myalgia': 2, 'I-Influenza': 2, 'I-Contracture_of_tendon_of_ankle_region': 2, 'B-Nonspecific_abdominal_symptom': 2, 'B-Chest_discomfort': 2, 'I-Chest_discomfort': 2, 'B-Blackout': 2, 'B-Clumsiness': 2, 'B-Hepatic_trauma': 2, 'B-Zestril': 2, 'B-Urinary_tract_infection': 2, 'B-Non-smoker': 2, 'I-Parvovirus_infection': 2, 'B-Failure_to_lose_weight': 2, 'B-Type_1_diabetes_mellitus': 2, 'I-Orchidodynia': 2, 'B-Derealisation': 2, 'B-Allergic_reaction': 2, 'I-Allergic_reaction': 2, 'B-Discolouration_of_skin': 2, 'I-Morning_stiffness_-_joint': 2, 'I-Disorder_of_muscle': 2, 'B-Unsteady_when_walking': 2, 'I-Abnormal_muscle_function': 2, 'I-Blepharospasm': 2, 'B-Jaundice': 2, 'B-Gallbladder_disorder': 2, 'I-Disorder_of_extremity': 2, 'B-soy_lecithin': 2, 'B-Rupture_of_tendon': 2, 'B-Rupture_of_Achilles_tendon': 2, 'B-Unable_to_stand': 2, 'B-Feels_hot': 2, 'I-Feels_hot': 2, 'I-Arthropathy_of_knee_joint': 2, 'I-Reduced_concentration': 2, 'B-Pain_in_thumb': 2, 'I-Heart_failure': 2, 'I-Degenerative_disorder_of_muscle': 2, 'B-Burning_sensation_of_vagina': 2, 'B-Mastalgia': 2, 'I-Mastalgia': 2, 'B-Erythema': 2, 'B-Lipitor_40_mg_tablet:_film-coated': 2, 'B-Urinary_retention': 2, 'I-Amyotrophic_lateral_sclerosis': 2, 'B-Feeling_intoxicated': 2, 'B-Difficulty_lifting': 2, 'B-Hammer_toe': 2, 'I-Hammer_toe': 2, 'B-White_blood_cell_count_abnormal': 2, 'I-Toe_swelling': 2, 'B-Injury_of_muscle': 2, 'I-Injury_of_muscle': 2, 'B-Swelling_of_hand': 2, 'I-Daily_headache': 2, 'B-Hives': 2, 'I-Congestion_of_throat': 2, 'I-Rapid_shallow_breathing': 2, 'B-Erectile_dysfunction': 2, 'B-Allergic_condition': 2, 'B-General_unsteadiness': 2, 'I-General_unsteadiness': 2, 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'I-Hand_eczema': 2, 'I-Vaginospasm': 2, 'I-Transient_global_amnesia': 2, 'B-Hepatomegaly': 1, 'I-Hepatomegaly': 1, 'B-B_Complex_(Cenovis)': 1, 'I-B_Complex_(Cenovis)': 1, 'B-Congestion_of_nasal_sinus': 1, 'I-Congestion_of_nasal_sinus': 1, 'B-Abnormal_liver_function': 1, 'B-Disorder_of_skin': 1, 'I-Disorder_of_skin': 1, 'B-Propensity_to_adverse_reactions_to_drug': 1, 'B-Glossitis': 1, 'B-Unable_to_walk_down_stairs': 1, 'B-Worried': 1, 'I-Worried': 1, 'B-atenolol': 1, 'B-Feeling_angry': 1, 'B-melatonin': 1, 'B-Contracture_of_tendon_of_ankle_region': 1, 'B-Abdominal_pressure': 1, 'I-Abdominal_pressure': 1, 'B-omeprazole': 1, 'I-Blackout': 1, 'B-Labyrinthitis': 1, 'B-Chronic_intractable_pain': 1, 'B-Periorbital_oedema': 1, 'I-Periorbital_oedema': 1, 'B-Falls': 1, 'I-Falls': 1, 'B-Motor_neurone_disease': 1, 'B-Plavix': 1, 'B-Collapse': 1, 'B-Urgent_desire_to_urinate': 1, 'B-Lyme_disease': 1, 'I-Lyme_disease': 1, 'B-Parvovirus_infection': 1, 'B-Ophthalmic_migraine': 1, 'I-Ophthalmic_migraine': 1, 'B-Orchidodynia': 1, 'B-Lip_swelling': 1, 'B-Epipen_Auto-Injector': 1, 'B-Morning_stiffness_-_joint': 1, 'B-Unable_to_make_a_fist': 1, 'B-Fosamax': 1, 'I-Fosamax': 1, 'B-Impairment_level_of_vision': 1, 'B-Abnormal_muscle_function': 1, 'B-Blepharospasm': 1, 'B-Severe_dehydration': 1, 'I-Severe_dehydration': 1, 'B-Abrasion_of_eye_region': 1, 'I-Abrasion_of_eye_region': 1, 'B-Basic_learning_problem': 1, 'I-Basic_learning_problem': 1, 'B-Right_upper_quadrant_pain': 1, 'B-Liver_function_tests_abnormal': 1, 'B-Cholestatic_jaundice_syndrome': 1, 'I-Cholestatic_jaundice_syndrome': 1, 'B-Disorder_of_extremity': 1, 'I-soy_lecithin': 1, 'B-Tenderness_of_upper_limb': 1, 'I-Tenderness_of_upper_limb': 1, 'B-Arthropathy_of_knee_joint': 1, 'B-Deteriorating_renal_function': 1, 'B-Cardiomyopathy': 1, 'B-Reduced_concentration': 1, 'B-Heart_failure': 1, 'B-Degenerative_disorder_of_muscle': 1, 'B-Cut_of_hand': 1, 'B-Malignant_tumour_of_colon': 1, 'I-Malignant_tumour_of_colon': 1, 'B-Hepatic_failure': 1, 'I-Hepatic_failure': 1, 'B-Stammering': 1, 'B-Obsessive-compulsive_disorder': 1, 'I-Obsessive-compulsive_disorder': 1, 'B-Chronic_pain': 1, 'I-Chronic_pain': 1, 'B-Mild_pain': 1, 'I-Mild_pain': 1, 'B-Enbrel': 1, 'I-Enbrel': 1, 'B-Bad_taste_in_mouth': 1, 'B-Neuroma_of_foot': 1, 'B-Disorder_of_back': 1, 'I-Disorder_of_back': 1, 'B-Pounding_heart': 1, 'B-Bowel_dysfunction': 1, 'I-Bowel_dysfunction': 1, 'B-Tendonitis_of_knee': 1, 'B-Toe_swelling': 1, 'B-Drinks_wine': 1, 'B-Gastrointestinal_tract_problem': 1, 'B-Neuropathy_of_upper_limb': 1, 'B-Daily_headache': 1, 'I-Hives': 1, 'B-Congestion_of_throat': 1, 'B-Rapid_shallow_breathing': 1, 'I-Erectile_dysfunction': 1, 'B-clonidine': 1, 'B-Cold_extremities': 1, 'I-Cold_extremities': 1, 'B-Decreased_range_of_shoulder_movement': 1, 'B-Involuntary_movement': 1, 'I-Involuntary_movement': 1, 'B-Dry_hair': 1, 'I-Dry_hair': 1, 'I-Lipidil': 1, 'B-Acenaesthesia': 1, 'B-Ulceration_of_colon': 1, 'B-Menstrual_loss_increasing': 1, 'B-Lumbar_facet_joint_pain': 1, 'B-Proximal_interphalangeal_joint_of_finger_pain': 1, 'B-Malignant_tumour_of_prostate': 1, 'I-Malignant_tumour_of_prostate': 1, 'B-Rupture_tendon_thigh': 1, 'B-Disorder_of_nasal_sinus': 1, 'I-Common_cold': 1, 'B-Abdominal_swelling': 1, 'I-Abdominal_swelling': 1, 'B-Uncontrollable_vomiting': 1, 'I-Uncontrollable_vomiting': 1, 'B-Swelling_of_lower_limb': 1, 'B-Pain_in_limb': 1, 'B-Throbbing_headache': 1, 'I-Throbbing_headache': 1, 'B-enalapril': 1, 'B-glibenclamide': 1, 'B-Avandia': 1, 'B-Deep_bruising': 1, 'I-Deep_bruising': 1, 'B-Pain_in_spine': 1, 'B-Bursitis_of_hip': 1, 'B-Excessive_and_frequent_menstruation': 1, 'B-Hearing_loss': 1, 'B-Chronic_rhinitis': 1, 'I-Chronic_rhinitis': 1, 'B-Upper_respiratory_tract_infection': 1, 'I-Drowsy': 1, 'B-Disturbance_in_speech_rhythm': 1, 'I-Disturbance_in_speech_rhythm': 1, 'B-Shuffling_gait': 1, 'I-Shuffling_gait': 1, 'B-Unable_to_get_out_of_a_chair': 1, 'B-Spots_on_skin': 1, 'B-Sacroiliac_joint_stiff': 1, 'B-Aortic_aneurysm': 1, 'I-Aortic_aneurysm': 1, 'B-Poor_peripheral_circulation': 1, 'I-Poor_peripheral_circulation': 1, 'B-Fragile_self-esteem': 1, 'B-Nasal_congestion': 1, 'I-Nasal_congestion': 1, 'B-Blocked_ears': 1, 'I-Blocked_ears': 1, 'B-Renal_calculus': 1, 'I-Renal_calculus': 1, 'B-Intra-abdominal_haematoma': 1, 'I-Intra-abdominal_haematoma': 1, 'B-Haemorrhage_of_abdominal_cavity_structure': 1, 'B-Immunosuppression': 1, 'B-Sense_of_smell_impaired': 1, 'B-Dysfunctional_uterine_bleeding': 1, 'B-Decreased_progesterone_level': 1, 'B-Dental_caries': 1, 'I-Dental_caries': 1, 'B-Autoimmune_disease': 1, 'B-Feeling_faint': 1, 'B-Impending_shock': 1, 'B-Gingival_disease': 1, 'I-Gingival_disease': 1, 'B-Premarin': 1, 'B-Fear_of_falling': 1, 'B-Unable_to_stand_up': 1, 'B-Reduction_of_bulk_of_muscle': 1, 'B-Loss_of_voice': 1, 'B-Respiratory_depression': 1, 'B-Tinea_pedis': 1, 'I-Low_motivation': 1, 'B-Abnormal_large_bowel_motility': 1, 'B-Irritable_bowel_syndrome_characterised_by_constipation': 1, 'B-Severe_vertigo': 1, 'I-Severe_vertigo': 1, 'B-Tendonitis_of_foot': 1, 'B-Dark_stools': 1, 'B-Difficulty_chewing': 1, 'B-Unsteady_when_standing': 1, 'B-Voltaren_Emulgel': 1, 'I-Voltaren_Emulgel': 1, 'B-Intraocular_haemorrhage': 1, 'I-Intraocular_haemorrhage': 1, 'I-Degenerative_disease_of_the_central_nervous_system': 1, 'B-Bunion': 1, 'B-Cold_foot': 1, 'B-Joint_tenderness': 1, 'I-Joint_tenderness': 1, 'B-Degeneration_of_intervertebral_disc': 1, 'I-Degeneration_of_intervertebral_disc': 1, 'B-Mild_cognitive_disorder': 1, 'I-Mild_cognitive_disorder': 1, 'B-Excitement': 1, 'I-Excitement': 1, 'B-Problem_of_visual_accommodation': 1, 'B-Arthralgia_of_the_upper_arm': 1, 'B-Increased_pressure': 1, 'I-Increased_pressure': 1, 'B-Burning_epigastric_pain': 1, 'B-Constantly_crying': 1, 'B-Heart_valve_regurgitation': 1, 'B-Goitre': 1, 'B-Oedema_of_finger': 1, 'B-Rupture_of_muscle': 1, 'B-Increased_belching': 1, 'I-Increased_belching': 1, 'B-C/O_-_feeling_depressed': 1, 'I-C/O_-_feeling_depressed': 1, 'B-fenofibrate_145_mg_tablet': 1, 'B-lysine': 1, 'B-vitamin_A': 1, 'I-vitamin_A': 1, 'B-Joint_laxity': 1, 'B-Feeling_high': 1, 'I-Feeling_high': 1, 'B-Fine_motor_impairment': 1, 'B-Lacks_confidence': 1, 'I-Syncope': 1, 'B-Productive_cough': 1, 'I-Productive_cough': 1, 'B-Malignant_tumour_of_spleen': 1, 'I-Malignant_tumour_of_spleen': 1, 'B-Arthritis_of_hip': 1, 'B-Type_II_diabetes_mellitus_uncontrolled': 1, 'B-Abnormal_weight_gain': 1, 'B-Acute_gastritis': 1, 'I-Acute_gastritis': 1, 'B-Abnormal_blood_pressure': 1, 'I-Abnormal_blood_pressure': 1, 'B-Stevens-Johnson_syndrome': 1, 'B-Buzzing_in_ear': 1, 'B-Elbow_joint_swelling': 1, 'I-Elbow_joint_swelling': 1, 'B-Mental_distress': 1, 'I-Mental_distress': 1, 'B-Repetitive_strain_injury': 1, 'B-Joint_swelling': 1, 'I-Joint_swelling': 1, 'B-Unable_to_run': 1, 'B-Finger_joint_locking': 1, 'I-Finger_joint_locking': 1, 'B-Impaired_mobility': 1, 'B-Infectious_disease_of_lung': 1, 'B-Malaria': 1, 'B-Impatient_character': 1, 'I-Impatient_character': 1, 'B-Difficulty_controlling_anger': 1, 'B-Gland_symptom': 1, 'I-Gland_symptom': 1, 'B-Cervical_arthritis': 1, 'B-Tires_quickly': 1, 'I-Tires_quickly': 1, 'B-Atacand': 1, 'B-Efexor-XR': 1, 'B-Encephalopathy': 1, 'I-Encephalopathy': 1, 'B-Glossopyrosis': 1, 'B-Scab_of_skin': 1, 'B-Furuncle': 1, 'B-Influenza-like_symptoms': 1, 'B-Increased_thirst': 1, 'B-Tunnel_vision': 1, 'I-Tunnel_vision': 1, 'B-Right_hemiparesis': 1, 'B-Transient_ischaemic_attack': 1, 'B-Intracranial_aneurysm': 1, 'I-Intracranial_aneurysm': 1, 'B-Dependance_on_walking_stick': 1, 'B-Cluster_headache': 1, 'I-Cluster_headache': 1, 'B-Nasonex_Aqueous': 1, 'I-Sciatica': 1, 'B-Abdominal_discomfort': 1, 'I-Abdominal_discomfort': 1, 'B-Ovarian_pain': 1, 'B-Pressure': 1, 'B-Burping': 1, 'I-Burping': 1, 'B-Arthropathy': 1, 'I-Arthropathy': 1, 'B-Generalised_pruritus': 1, 'B-lisinopril': 1, 'B-hydrochlorothiazide': 1, 'B-Arthritis_of_shoulder_region_joint': 1, 'B-Scleral_icterus': 1, 'I-Scleral_icterus': 1, 'B-Facial_spasm': 1, 'B-Difficulty_moving_hand': 1, 'I-glucosamine': 1, 'B-Epigastric_discomfort': 1, 'B-Arthralgia_of_multiple_joints': 1, 'B-Decreased_muscle_tone': 1, 'B-Oxycontin': 1, 'B-Xanax': 1, 'I-Infection': 1, 'B-Acne': 1, 'B-Joint_pain': 1, 'B-Thyroid_disease': 1, 'I-Thyroid_disease': 1, 'B-Visual_field_scotoma': 1, 'I-Visual_field_scotoma': 1, 'B-Absent_minded': 1, 'B-Metabolic_syndrome_X': 1, 'I-Metabolic_syndrome_X': 1, 'B-Oedema_of_extremity': 1, 'B-Dyssomnia': 1, 'I-Dyssomnia': 1, 'B-Tightness_in_arm': 1, 'B-Tongue_swelling': 1, 'I-Tongue_swelling': 1, 'B-Elevated_cholesterol/high_density_lipoprotein_ratio': 1, 'B-Disorder_of_face': 1, 'B-Depressed_mood': 1, 'I-Depressed_mood': 1, 'B-Loss_of_confidence': 1, 'B-Swelling_of_upper_limb': 1, 'B-Contusion_of_hand': 1, 'B-Otalgia': 1, 'I-Otalgia': 1, 'B-Poor_balance': 1, 'I-Poor_balance': 1, 'B-Cozaar': 1, 'B-bisoprolol': 1, 'B-Abnormal_gait': 1, 'B-Premenstrual_tension_syndrome': 1, 'I-Premenstrual_tension_syndrome': 1, 'I-Hyperactive_bowel_sounds': 1, 'B-Tagamet': 1, 'B-Craving_for_food_or_drink': 1, 'I-Craving_for_food_or_drink': 1, 'B-Night_pain': 1, 'B-Large_breast': 1, 'B-naproxen': 1, 'I-naproxen': 1, 'B-Lyrica': 1, 'B-pseudoephedrine': 1, 'B-Dislocation_of_joint': 1, 'B-Clicking_interphalangeal_joint_of_toe': 1, 'B-Clicking_knee': 1, 'B-Symptom_of_ankle': 1, 'B-Unable_to_lie_down': 1, 'B-Thoughts_of_self_harm': 1, 'B-Increased_lactic_acid_level': 1, 'I-Nightmares': 1, 'B-Calcaneal_spur': 1, 'I-Calcaneal_spur': 1, 'B-Severe_visual_impairment': 1, 'B-Pain_in_right_arm': 1, 'I-Watery_eye': 1, 'B-High_pain_threshold': 1, 'B-Gastric_ulcer_with_perforation': 1, 'I-Gastric_ulcer_with_perforation': 1, 'B-Peritonitis': 1, 'B-Bacterial_sepsis': 1, 'B-Respiratory_failure': 1, 'I-Respiratory_failure': 1, 'B-Bumping_heart': 1, 'B-Gingival_oedema': 1, 'I-Gingival_oedema': 1, 'B-Abnormal_vision': 1, 'I-Abnormal_vision': 1, 'I-Hungry': 1, 'B-Endometriosis_of_uterus': 1, 'B-Blood_coagulation_disorder': 1, 'B-Ehlers-Danlos_syndrome': 1, 'B-Disorder_of_vision': 1, 'I-prednisone': 1, 'B-Rupture_of_tendon_of_lower_leg_and_ankle': 1, 'B-Solaraze': 1, 'B-Muscle_injury': 1, 'B-Warm_hands': 1, 'B-ibuprofen_5%_gel': 1, 'I-ibuprofen_5%_gel': 1, 'B-Skin_tenderness': 1, 'B-Compression_neuropathy_of_trunk': 1, 'B-Hyperaesthesia': 1, 'B-Intermittent_pain': 1, 'I-Intermittent_pain': 1, 'B-testosterone': 1, 'B-Deseril': 1, 'B-Has_delayed_recall': 1, 'B-Impaired_bed_mobility': 1, 'B-Pain_in_forearm': 1, 'B-Muscle_fasciculation': 1, 'B-Breast_tenderness': 1, 'I-Breast_tenderness': 1, 'B-Polyarthritis_associated_with_another_disorder': 1, 'I-Polyarthritis_associated_with_another_disorder': 1, 'B-Cataract': 1, 'B-Lumbar_arthritis': 1, 'B-Blurring_of_visual_image': 1, 'B-Decreased_venous_pressure': 1, 'B-Palpitations_-_rapid': 1, 'I-Palpitations_-_rapid': 1, 'B-Dehydration': 1, 'B-Photosensitivity': 1, 'B-Rhinocort_Aqueous': 1, 'B-Sexual_dysfunction': 1, 'I-Sexual_dysfunction': 1, 'I-atorvastatin': 1, 'B-Senility': 1, 'B-Intolerant_of_cold': 1, 'B-ramipril': 1, 'B-Disturbance_in_physical_behaviour': 1, 'B-Bed-ridden': 1, 'B-Unable_to_feed_self': 1, 'B-Feeling_nervous': 1, 'B-Knee_joint_painful_on_movement': 1, 'B-Ill-at-ease': 1, 'B-Night_sweats': 1, 'I-Night_sweats': 1, 'I-Hyperactive_behaviour': 1, 'B-Mentally_alert': 1, 'I-Mentally_alert': 1, 'B-Sudden_visual_loss': 1, 'B-Pain_in_the_coccyx': 1, 'I-Pain_in_the_coccyx': 1, 'B-Irregular_heart_rate': 1, 'B-Difficulty_writing': 1, 'B-Parkinsonism': 1, 'B-Nasal_discharge': 1, 'I-Nasal_discharge': 1, 'B-Decreased_testosterone_level': 1, 'I-Decreased_testosterone_level': 1, 'B-Rupture_of_anterior_cruciate_ligament': 1, 'I-Rupture_of_anterior_cruciate_ligament': 1, 'B-Nexium': 1, 'B-Disability': 1, 'B-Numbness_of_toe': 1, 'I-Menstrual_spotting': 1, 'B-Injury_of_tendon_of_the_rotator_cuff_of_shoulder': 1, 'B-Shoulder_girdle_weakness': 1, 'B-Weakness_of_back': 1, 'B-Weakness_of_neck': 1, 'B-Unable_to_move_all_four_limbs': 1, 'B-Labour_pain': 1, 'I-Labour_pain': 1, 'B-diclofenac_+_misoprostol': 1, 'B-Ankle_joint_pain': 1, 'B-Parkinsonian_tremor': 1, 'B-Celebrex_200_mg_capsule:_hard': 1, 'I-Celebrex_200_mg_capsule:_hard': 1, 'B-meloxicam': 1, 'B-caffeine': 1, 'B-Irregular_bowel_habits': 1, 'I-Irregular_bowel_habits': 1, 'B-paracetamol_+_ibuprofen': 1, 'I-paracetamol_+_ibuprofen': 1, 'B-Hypomenorrhoea': 1, 'B-methylprednisolone': 1, 'B-Dysphagia': 1, 'B-Coma': 1, 'B-Difficulty_getting_out_of_a_chair': 1, 'B-Eruption': 1, 'I-Eruption': 1, 'B-Blind_or_low_vision_-_one_eye_only': 1, 'B-Loss_of_equilibrium': 1, 'B-Always_sleepy': 1, 'B-Wheezing': 1, 'B-Reduced_visual_acuity': 1, 'I-Reduced_visual_acuity': 1, 'B-Diplopia': 1, 'I-Diplopia': 1, 'B-Poor_muscle_tone': 1, 'B-Feeling_bad': 1, 'I-Feeling_bad': 1, 'B-Isolated_memory_skills': 1, 'B-Rotator_cuff_syndrome': 1, 'B-Unable_to_move_hand': 1, 'I-Bloating_symptom': 1, 'B-amlodipine': 1, 'B-Swollen_feet': 1, 'I-Feeling_agitated': 1, 'B-Unable_to_bend_down': 1, 'B-Cramping_pain': 1, 'I-Cramping_pain': 1, 'B-Intracranial_tumour': 1, 'I-Intracranial_tumour': 1, 'B-Hypercholesterolaemia': 1, 'B-Restlessness': 1, 'B-Emotional_upset': 1, 'B-Viral_upper_respiratory_tract_infection': 1, 'B-zinc': 1, 'B-Zantac': 1, 'B-Mental_disorder': 1, 'I-Mental_disorder': 1, 'B-Pruritus_ani': 1, 'I-Pruritus_ani': 1, 'B-Paraesthesia_of_upper_limb': 1, 'B-Iliotibial_band_friction_syndrome': 1, 'B-Malaise_and_fatigue': 1, 'B-Panadeine': 1, 'B-codeine_+_ibuprofen': 1, 'I-codeine_+_ibuprofen': 1, 'B-Voltaren_Rapid_25_mg_tablet:_sugar-coated': 1, 'B-Stumbling_gait': 1, 'B-Lescol': 1, 'I-Irritable_bowel_syndrome': 1, 'I-Indigestion': 1, 'B-Psychotic_disorder': 1, 'B-Seroquel': 1, 'B-Sweating_problem': 1, 'I-Sweating_problem': 1, 'B-Immobile': 1, 'I-Immobile': 1, 'B-Arthritis/arthrosis': 1, 'B-Neuralgia': 1, 'I-Neuralgia': 1, 'B-Prinivil': 1, 'B-Shin_splint': 1, 'B-Right_ventricular_dilatation': 1, 'B-Raised_serum_calcium_level': 1, 'I-Raised_serum_calcium_level': 1, 'B-Disorder_of_cardiac_function': 1, 'B-magnesium': 1, 'B-Feeling_content': 1, 'B-Bleeding_from_nose': 1, 'I-Bleeding_from_nose': 1, 'B-Nocturnal_enuresis': 1, 'I-Nocturnal_enuresis': 1, 'B-Numbness_of_finger': 1, 'B-Difficulty_gripping': 1, 'B-Eye_strain': 1, 'B-Unable_to_sit': 1, 'B-Abdominal_hyperaesthesia': 1, 'B-Difficulty_moving_arm': 1, 'B-Feeling_agitated_232_249': 1, 'I-Feeling_agitated_232_249': 1, 'B-Unable_to_control_anger': 1, 'B-Disorder_of_tendon': 1, 'B-Tendon_contracture': 1, 'I-Tendon_contracture': 1, 'B-Derangement_of_meniscus': 1, 'I-Derangement_of_meniscus': 1, 'B-Cardiovascular_disease': 1, 'I-Cardiovascular_disease': 1, 'B-Prolonged_periods': 1, 'B-Bad_circulation_-_vasomotor_change': 1, 'I-Bad_circulation_-_vasomotor_change': 1, 'B-Pain_provoked_by_rest': 1, 'B-Chronic_diarrhoea': 1, 'I-Chronic_diarrhoea': 1, 'B-Ulcerative_colitis': 1, 'I-Ulcerative_colitis': 1, 'B-Angina': 1, 'I-Angina': 1, 'I-Lupus_erythematosus': 1, 'B-Capoten': 1, 'B-glipizide': 1, 'B-tramadol': 1, 'B-Not_getting_enough_sleep': 1, 'B-Myalgia/myositis_-_multiple': 1, 'B-White_discolouration_of_skin': 1, 'B-Difficulty_dressing': 1, 'B-Traumatic_blister_of_mouth': 1, 'B-Abdominal_distension': 1, 'B-Pain_in_cheek': 1, 'B-pyridoxine': 1, 'B-Increased_albumin': 1, 'B-Gingivitis': 1, 'I-Gingivitis': 1, 'B-Post_traumatic_osteoarthritis': 1, 'B-Dropped_beats_-_heart': 1, 'B-Cardiac_arrhythmia': 1, 'I-Cardiac_arrhythmia': 1, 'B-Pain_of_uterus': 1, 'B-Anxiety_attack': 1, 'B-Difficulty_riding_a_bicycle': 1, 'B-Difficulty_standing': 1, 'B-Foot_eczema': 1, 'B-Hand_eczema': 1, 'B-Hypochondriasis': 1, 'B-Vaginospasm': 1, 'B-Knee_joint_inflamed': 1, 'I-Knee_joint_inflamed': 1, 'B-Sinus_pain': 1, 'I-Sinus_pain': 1, 'B-Voltaren_Rapid': 1, 'I-Voltaren_Rapid': 1, 'B-Skin_nodule': 1, 'B-Stress_overload': 1, 'I-Stress_overload': 1, 'B-Feeling_hopeless': 1, 'B-Feeling_lonely': 1, 'B-Poor_self-image': 1, 'I-Poor_self-image': 1, 'B-Morbid_thoughts': 1, 'B-Feels_everything_is_futile': 1, 'B-Transient_global_amnesia': 1})\n"
     ]
    }
   ],
   "source": [
    "# get all unique ner tags, excluding leading conll ordering term\n",
    "ner_tags = []\n",
    "for doc in train_docs:\n",
    "    for token in doc:\n",
    "        labels = get_all_labels(token)\n",
    "        if \"ner\" in labels:\n",
    "            for label in labels[\"ner\"]:\n",
    "                ner_tags.append(label.value)\n",
    "\n",
    "# get all unique meddra tags, excluding leading conll ordering term\n",
    "meddra_tags = []\n",
    "for doc in train_docs:\n",
    "    for token in doc:\n",
    "        labels = get_all_labels(token)\n",
    "        if \"meddra\" in labels:\n",
    "            for label in labels[\"meddra\"]:\n",
    "                meddra_tags.append(label.value)\n",
    "ner_tags = Counter(ner_tags)\n",
    "del ner_tags['O']\n",
    "meddra_tags = Counter(meddra_tags)\n",
    "del meddra_tags['O']\n",
    "\n",
    "ner_tags_ordered = [a[0] for a in ner_tags.most_common()]\n",
    "meddra_tags_ordered = [a[0] for a in meddra_tags.most_common()]\n",
    "\n",
    "print(\"Unique NER tags:\", ner_tags)\n",
    "print(\"Unique Meddra tags:\", meddra_tags)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ner_tags)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tab = pd.DataFrame([[a, b] for a,b in ner_tags.items()], columns = ['NER tag','count'])\n",
    "tab = tab.sort_values('count',ascending=False)\n",
    "\n",
    "\n",
    "sns.set(rc={'figure.figsize':(10,6)})\n",
    "chart = sns.barplot(tab, x='NER tag',y='count')\n",
    "chart.set_xticklabels(chart.get_xticklabels(), rotation=60, horizontalalignment='right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tab = pd.DataFrame([[a, b] for a,b in meddra_tags.items()], columns = ['mapped term','count'])\n",
    "tab = tab.sort_values('count',ascending=False)\n",
    "\n",
    "sns.set(rc={'figure.figsize':(10,6)})\n",
    "chart = sns.barplot(tab[:20], x='mapped term',y='count')\n",
    "chart.set_xticklabels(chart.get_xticklabels(), rotation=60, horizontalalignment='right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mapped term</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>B-Lipitor</td>\n",
       "      <td>825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>I-CONCEPT_LESS</td>\n",
       "      <td>746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>I-Severe_pain</td>\n",
       "      <td>425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>B-CONCEPT_LESS</td>\n",
       "      <td>351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>I-Myalgia</td>\n",
       "      <td>296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1302</th>\n",
       "      <td>I-naproxen</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>786</th>\n",
       "      <td>B-Nasal_congestion</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1304</th>\n",
       "      <td>B-Lyrica</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1306</th>\n",
       "      <td>B-pseudoephedrine</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>714</th>\n",
       "      <td>I-Uncontrollable_vomiting</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1748 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    mapped term  count\n",
       "6                     B-Lipitor    825\n",
       "49               I-CONCEPT_LESS    746\n",
       "1                 I-Severe_pain    425\n",
       "43               B-CONCEPT_LESS    351\n",
       "100                   I-Myalgia    296\n",
       "...                         ...    ...\n",
       "1302                 I-naproxen      1\n",
       "786          B-Nasal_congestion      1\n",
       "1304                   B-Lyrica      1\n",
       "1306          B-pseudoephedrine      1\n",
       "714   I-Uncontrollable_vomiting      1\n",
       "\n",
       "[1748 rows x 2 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "def repeat_arr(lst, n):\n",
    "    if len(lst) < n:\n",
    "        lst *= (n // len(lst)) + 1\n",
    "    return lst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "def remove_o_tags(y_true, y_pred):\n",
    "    # y_true_no_o = []\n",
    "    # y_pred_no_o = []\n",
    "    # for true, pred in zip(y_true, y_pred):\n",
    "    #     if true != 'O':\n",
    "    #         y_true_no_o.append(true)\n",
    "    #         y_pred_no_o.append(pred)\n",
    "    # return y_true_no_o, y_pred_no_o\n",
    "    \n",
    "    return y_true, y_pred\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ner - random baseline"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ner - most frequent baseline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 948/948 [00:09<00:00, 103.82it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I-ADR\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 119/119 [00:00<00:00, 125.46it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I-ADR\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 119/119 [00:00<00:00, 128.98it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I-ADR\n"
     ]
    }
   ],
   "source": [
    "res_random = res_mostfreq = pd.DataFrame(columns=['split','index']+ner_tags_ordered)\n",
    "train=None\n",
    "for split, split_name in [(train_docs,'train'),(dev_docs,'dev'),(test_docs,'test')]:\n",
    "    y_true = []\n",
    "    for doc in tqdm(split, total=len(split)):\n",
    "        for token in doc:\n",
    "            labels = get_all_labels(token)\n",
    "            y_true += [a.value for a in labels['ner']]\n",
    "            \n",
    "    if split_name == 'train':\n",
    "        train = y_true\n",
    "            \n",
    "    np.random.seed(1234)\n",
    "    y_pred = random.sample(repeat_arr(sorted(ner_tags_ordered+['O']), len(y_true)), len(y_true))\n",
    "    y_true1, y_pred1 = remove_o_tags(y_true, y_pred)\n",
    "    res = pd.DataFrame.from_dict(classification_report(y_true1, y_pred1, output_dict=True, zero_division=0)).reset_index()\n",
    "    temp = res['index']\n",
    "    res.drop('index',axis=1,inplace=True)\n",
    "    res.insert(loc=0, column='split', value=split_name)\n",
    "    res.insert(loc=1, column='index', value=temp)\n",
    "    res_random = pd.concat([res_random, res],ignore_index=True)\n",
    "    \n",
    "    mostfreq = ner_tags_ordered[0]\n",
    "    print(mostfreq)\n",
    "    y_pred = [mostfreq]*len(y_true)\n",
    "    y_true1, y_pred1 = remove_o_tags(y_true, y_pred)\n",
    "    res = pd.DataFrame.from_dict(classification_report(y_true1, y_pred1, output_dict=True, zero_division=0)).reset_index()\n",
    "    temp = res['index']\n",
    "    res.drop('index',axis=1,inplace=True)\n",
    "    res.insert(loc=0, column='split', value=split_name)\n",
    "    res.insert(loc=1, column='index', value=temp)\n",
    "    res_mostfreq = pd.concat([res_mostfreq, res],ignore_index=True)\n",
    "\n",
    "if 'O' in res_random.columns:\n",
    "    res_random.drop('O',axis=1,inplace=True)\n",
    "if 'O' in res_mostfreq.columns:\n",
    "    res_mostfreq.drop('O',axis=1,inplace=True)\n",
    "\n",
    "res_random = res_random.iloc[:, :res_random.columns.get_loc('weighted avg')+1]\n",
    "res_mostfreq = res_mostfreq.iloc[:, :res_mostfreq.columns.get_loc('weighted avg')+1]\n",
    "\n",
    "res_random.to_csv('baseline_ner_model'+suf+'/random_classification_report.csv',index=False)\n",
    "res_mostfreq.to_csv('baseline_ner_model'+suf+'/mostfreq_classification_report.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>split</th>\n",
       "      <th>index</th>\n",
       "      <th>I-ADR</th>\n",
       "      <th>B-ADR</th>\n",
       "      <th>B-Drug</th>\n",
       "      <th>I-Finding</th>\n",
       "      <th>B-Finding</th>\n",
       "      <th>B-Disease</th>\n",
       "      <th>B-Symptom</th>\n",
       "      <th>I-Symptom</th>\n",
       "      <th>I-Disease</th>\n",
       "      <th>I-Drug</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>macro avg</th>\n",
       "      <th>weighted avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>train</td>\n",
       "      <td>precision</td>\n",
       "      <td>0.091215</td>\n",
       "      <td>0.050366</td>\n",
       "      <td>0.012071</td>\n",
       "      <td>0.003714</td>\n",
       "      <td>0.003830</td>\n",
       "      <td>0.002437</td>\n",
       "      <td>0.002089</td>\n",
       "      <td>0.001857</td>\n",
       "      <td>0.001973</td>\n",
       "      <td>0.001741</td>\n",
       "      <td>0.091531</td>\n",
       "      <td>0.091530</td>\n",
       "      <td>0.707337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>train</td>\n",
       "      <td>recall</td>\n",
       "      <td>0.098831</td>\n",
       "      <td>0.092105</td>\n",
       "      <td>0.074499</td>\n",
       "      <td>0.091691</td>\n",
       "      <td>0.106796</td>\n",
       "      <td>0.090909</td>\n",
       "      <td>0.081081</td>\n",
       "      <td>0.073394</td>\n",
       "      <td>0.100592</td>\n",
       "      <td>0.093168</td>\n",
       "      <td>0.091531</td>\n",
       "      <td>0.090375</td>\n",
       "      <td>0.091531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>train</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.094870</td>\n",
       "      <td>0.065121</td>\n",
       "      <td>0.020775</td>\n",
       "      <td>0.007139</td>\n",
       "      <td>0.007394</td>\n",
       "      <td>0.004747</td>\n",
       "      <td>0.004073</td>\n",
       "      <td>0.003623</td>\n",
       "      <td>0.003870</td>\n",
       "      <td>0.003419</td>\n",
       "      <td>0.091531</td>\n",
       "      <td>0.034478</td>\n",
       "      <td>0.148582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>train</td>\n",
       "      <td>support</td>\n",
       "      <td>7953.000000</td>\n",
       "      <td>4712.000000</td>\n",
       "      <td>1396.000000</td>\n",
       "      <td>349.000000</td>\n",
       "      <td>309.000000</td>\n",
       "      <td>231.000000</td>\n",
       "      <td>222.000000</td>\n",
       "      <td>218.000000</td>\n",
       "      <td>169.000000</td>\n",
       "      <td>161.000000</td>\n",
       "      <td>0.091531</td>\n",
       "      <td>94777.000000</td>\n",
       "      <td>94777.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>dev</td>\n",
       "      <td>precision</td>\n",
       "      <td>0.076592</td>\n",
       "      <td>0.037866</td>\n",
       "      <td>0.015517</td>\n",
       "      <td>0.002584</td>\n",
       "      <td>0.009466</td>\n",
       "      <td>0.003448</td>\n",
       "      <td>0.001721</td>\n",
       "      <td>0.001721</td>\n",
       "      <td>0.002586</td>\n",
       "      <td>0.003442</td>\n",
       "      <td>0.090333</td>\n",
       "      <td>0.090287</td>\n",
       "      <td>0.710685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>dev</td>\n",
       "      <td>recall</td>\n",
       "      <td>0.092133</td>\n",
       "      <td>0.067588</td>\n",
       "      <td>0.097826</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.171875</td>\n",
       "      <td>0.129032</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>0.107143</td>\n",
       "      <td>0.148148</td>\n",
       "      <td>0.090333</td>\n",
       "      <td>0.099619</td>\n",
       "      <td>0.090333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>dev</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.083647</td>\n",
       "      <td>0.048538</td>\n",
       "      <td>0.026786</td>\n",
       "      <td>0.004938</td>\n",
       "      <td>0.017945</td>\n",
       "      <td>0.006717</td>\n",
       "      <td>0.003370</td>\n",
       "      <td>0.003339</td>\n",
       "      <td>0.005051</td>\n",
       "      <td>0.006728</td>\n",
       "      <td>0.090333</td>\n",
       "      <td>0.033741</td>\n",
       "      <td>0.146912</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>dev</td>\n",
       "      <td>support</td>\n",
       "      <td>966.000000</td>\n",
       "      <td>651.000000</td>\n",
       "      <td>184.000000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>0.090333</td>\n",
       "      <td>12775.000000</td>\n",
       "      <td>12775.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>test</td>\n",
       "      <td>precision</td>\n",
       "      <td>0.068966</td>\n",
       "      <td>0.050186</td>\n",
       "      <td>0.013928</td>\n",
       "      <td>0.004647</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002786</td>\n",
       "      <td>0.002788</td>\n",
       "      <td>0.002786</td>\n",
       "      <td>0.000929</td>\n",
       "      <td>0.004647</td>\n",
       "      <td>0.088712</td>\n",
       "      <td>0.088798</td>\n",
       "      <td>0.694846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>test</td>\n",
       "      <td>recall</td>\n",
       "      <td>0.076525</td>\n",
       "      <td>0.093750</td>\n",
       "      <td>0.068493</td>\n",
       "      <td>0.138889</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.150000</td>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.090909</td>\n",
       "      <td>0.083333</td>\n",
       "      <td>0.096154</td>\n",
       "      <td>0.088712</td>\n",
       "      <td>0.093136</td>\n",
       "      <td>0.088712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>test</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.072549</td>\n",
       "      <td>0.065375</td>\n",
       "      <td>0.023148</td>\n",
       "      <td>0.008993</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005469</td>\n",
       "      <td>0.005464</td>\n",
       "      <td>0.005405</td>\n",
       "      <td>0.001837</td>\n",
       "      <td>0.008865</td>\n",
       "      <td>0.088712</td>\n",
       "      <td>0.032685</td>\n",
       "      <td>0.144769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>test</td>\n",
       "      <td>support</td>\n",
       "      <td>967.000000</td>\n",
       "      <td>576.000000</td>\n",
       "      <td>219.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>0.088712</td>\n",
       "      <td>11836.000000</td>\n",
       "      <td>11836.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    split      index        I-ADR        B-ADR       B-Drug   I-Finding   \n",
       "0   train  precision     0.091215     0.050366     0.012071    0.003714  \\\n",
       "1   train     recall     0.098831     0.092105     0.074499    0.091691   \n",
       "2   train   f1-score     0.094870     0.065121     0.020775    0.007139   \n",
       "3   train    support  7953.000000  4712.000000  1396.000000  349.000000   \n",
       "4     dev  precision     0.076592     0.037866     0.015517    0.002584   \n",
       "5     dev     recall     0.092133     0.067588     0.097826    0.055556   \n",
       "6     dev   f1-score     0.083647     0.048538     0.026786    0.004938   \n",
       "7     dev    support   966.000000   651.000000   184.000000   54.000000   \n",
       "8    test  precision     0.068966     0.050186     0.013928    0.004647   \n",
       "9    test     recall     0.076525     0.093750     0.068493    0.138889   \n",
       "10   test   f1-score     0.072549     0.065375     0.023148    0.008993   \n",
       "11   test    support   967.000000   576.000000   219.000000   36.000000   \n",
       "\n",
       "     B-Finding   B-Disease   B-Symptom   I-Symptom   I-Disease      I-Drug   \n",
       "0     0.003830    0.002437    0.002089    0.001857    0.001973    0.001741  \\\n",
       "1     0.106796    0.090909    0.081081    0.073394    0.100592    0.093168   \n",
       "2     0.007394    0.004747    0.004073    0.003623    0.003870    0.003419   \n",
       "3   309.000000  231.000000  222.000000  218.000000  169.000000  161.000000   \n",
       "4     0.009466    0.003448    0.001721    0.001721    0.002586    0.003442   \n",
       "5     0.171875    0.129032    0.080000    0.055556    0.107143    0.148148   \n",
       "6     0.017945    0.006717    0.003370    0.003339    0.005051    0.006728   \n",
       "7    64.000000   31.000000   25.000000   36.000000   28.000000   27.000000   \n",
       "8     0.000000    0.002786    0.002788    0.002786    0.000929    0.004647   \n",
       "9     0.000000    0.150000    0.136364    0.090909    0.083333    0.096154   \n",
       "10    0.000000    0.005469    0.005464    0.005405    0.001837    0.008865   \n",
       "11   52.000000   20.000000   22.000000   33.000000   12.000000   52.000000   \n",
       "\n",
       "    accuracy     macro avg  weighted avg  \n",
       "0   0.091531      0.091530      0.707337  \n",
       "1   0.091531      0.090375      0.091531  \n",
       "2   0.091531      0.034478      0.148582  \n",
       "3   0.091531  94777.000000  94777.000000  \n",
       "4   0.090333      0.090287      0.710685  \n",
       "5   0.090333      0.099619      0.090333  \n",
       "6   0.090333      0.033741      0.146912  \n",
       "7   0.090333  12775.000000  12775.000000  \n",
       "8   0.088712      0.088798      0.694846  \n",
       "9   0.088712      0.093136      0.088712  \n",
       "10  0.088712      0.032685      0.144769  \n",
       "11  0.088712  11836.000000  11836.000000  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res_random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>split</th>\n",
       "      <th>index</th>\n",
       "      <th>I-ADR</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>train</td>\n",
       "      <td>precision</td>\n",
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       "      <th>1</th>\n",
       "      <td>train</td>\n",
       "      <td>recall</td>\n",
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       "      <td>0.090909</td>\n",
       "      <td>0.083913</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>train</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.154833</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.083913</td>\n",
       "      <td>0.014076</td>\n",
       "      <td>0.012992</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>train</td>\n",
       "      <td>support</td>\n",
       "      <td>7953.000000</td>\n",
       "      <td>4712.0</td>\n",
       "      <td>1396.0</td>\n",
       "      <td>349.0</td>\n",
       "      <td>309.0</td>\n",
       "      <td>231.0</td>\n",
       "      <td>222.0</td>\n",
       "      <td>218.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>0.083913</td>\n",
       "      <td>94777.000000</td>\n",
       "      <td>94777.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>dev</td>\n",
       "      <td>precision</td>\n",
       "      <td>0.075616</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.075616</td>\n",
       "      <td>0.006874</td>\n",
       "      <td>0.005718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>dev</td>\n",
       "      <td>recall</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.075616</td>\n",
       "      <td>0.090909</td>\n",
       "      <td>0.075616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>dev</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.140601</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.075616</td>\n",
       "      <td>0.012782</td>\n",
       "      <td>0.010632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>dev</td>\n",
       "      <td>support</td>\n",
       "      <td>966.000000</td>\n",
       "      <td>651.0</td>\n",
       "      <td>184.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.075616</td>\n",
       "      <td>12775.000000</td>\n",
       "      <td>12775.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>test</td>\n",
       "      <td>precision</td>\n",
       "      <td>0.081700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.081700</td>\n",
       "      <td>0.007427</td>\n",
       "      <td>0.006675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>test</td>\n",
       "      <td>recall</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.081700</td>\n",
       "      <td>0.090909</td>\n",
       "      <td>0.081700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>test</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.151058</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.081700</td>\n",
       "      <td>0.013733</td>\n",
       "      <td>0.012341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>test</td>\n",
       "      <td>support</td>\n",
       "      <td>967.000000</td>\n",
       "      <td>576.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.081700</td>\n",
       "      <td>11836.000000</td>\n",
       "      <td>11836.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    split      index        I-ADR   B-ADR  B-Drug  I-Finding  B-Finding   \n",
       "0   train  precision     0.083913     0.0     0.0        0.0        0.0  \\\n",
       "1   train     recall     1.000000     0.0     0.0        0.0        0.0   \n",
       "2   train   f1-score     0.154833     0.0     0.0        0.0        0.0   \n",
       "3   train    support  7953.000000  4712.0  1396.0      349.0      309.0   \n",
       "4     dev  precision     0.075616     0.0     0.0        0.0        0.0   \n",
       "5     dev     recall     1.000000     0.0     0.0        0.0        0.0   \n",
       "6     dev   f1-score     0.140601     0.0     0.0        0.0        0.0   \n",
       "7     dev    support   966.000000   651.0   184.0       54.0       64.0   \n",
       "8    test  precision     0.081700     0.0     0.0        0.0        0.0   \n",
       "9    test     recall     1.000000     0.0     0.0        0.0        0.0   \n",
       "10   test   f1-score     0.151058     0.0     0.0        0.0        0.0   \n",
       "11   test    support   967.000000   576.0   219.0       36.0       52.0   \n",
       "\n",
       "    B-Disease  B-Symptom  I-Symptom  I-Disease  I-Drug  accuracy   \n",
       "0         0.0        0.0        0.0        0.0     0.0  0.083913  \\\n",
       "1         0.0        0.0        0.0        0.0     0.0  0.083913   \n",
       "2         0.0        0.0        0.0        0.0     0.0  0.083913   \n",
       "3       231.0      222.0      218.0      169.0   161.0  0.083913   \n",
       "4         0.0        0.0        0.0        0.0     0.0  0.075616   \n",
       "5         0.0        0.0        0.0        0.0     0.0  0.075616   \n",
       "6         0.0        0.0        0.0        0.0     0.0  0.075616   \n",
       "7        31.0       25.0       36.0       28.0    27.0  0.075616   \n",
       "8         0.0        0.0        0.0        0.0     0.0  0.081700   \n",
       "9         0.0        0.0        0.0        0.0     0.0  0.081700   \n",
       "10        0.0        0.0        0.0        0.0     0.0  0.081700   \n",
       "11       20.0       22.0       33.0       12.0    52.0  0.081700   \n",
       "\n",
       "       macro avg  weighted avg  \n",
       "0       0.007628      0.007041  \n",
       "1       0.090909      0.083913  \n",
       "2       0.014076      0.012992  \n",
       "3   94777.000000  94777.000000  \n",
       "4       0.006874      0.005718  \n",
       "5       0.090909      0.075616  \n",
       "6       0.012782      0.010632  \n",
       "7   12775.000000  12775.000000  \n",
       "8       0.007427      0.006675  \n",
       "9       0.090909      0.081700  \n",
       "10      0.013733      0.012341  \n",
       "11  11836.000000  11836.000000  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res_mostfreq"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## meddra - random baseline"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## meddra - most frequent baseline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 948/948 [00:08<00:00, 107.54it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B-Lipitor\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 119/119 [00:00<00:00, 139.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B-Lipitor\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 119/119 [00:00<00:00, 137.89it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B-Lipitor\n"
     ]
    }
   ],
   "source": [
    "res_random = res_mostfreq = pd.DataFrame(columns=['split','index']+meddra_tags_ordered)\n",
    "train=None\n",
    "for split, split_name in [(train_docs,'train'),(dev_docs,'dev'),(test_docs,'test')]:\n",
    "    y_true = []\n",
    "    for doc in tqdm(split, total=len(split)):\n",
    "        for token in doc:\n",
    "            labels = get_all_labels(token)\n",
    "            y_true += [a.value for a in labels['meddra']]\n",
    "    \n",
    "    if split_name == 'train':\n",
    "        train = y_true\n",
    "    \n",
    "    np.random.seed(1234)\n",
    "    y_pred = random.sample(repeat_arr(sorted(meddra_tags_ordered+['O']), len(y_true)), len(y_true))\n",
    "    y_true1, y_pred1 = remove_o_tags(y_true, y_pred)\n",
    "    res = pd.DataFrame.from_dict(classification_report(y_true1, y_pred1, output_dict=True, zero_division=0)).reset_index()\n",
    "    temp = res['index']\n",
    "    res.drop('index',axis=1,inplace=True)\n",
    "    res.insert(loc=0, column='split', value=split_name)\n",
    "    res.insert(loc=1, column='index', value=temp)\n",
    "    res_random = pd.concat([res_random, res],ignore_index=True)\n",
    "    \n",
    "    mostfreq = meddra_tags_ordered[0]\n",
    "    print(mostfreq)\n",
    "    y_pred = [mostfreq]*len(y_true)\n",
    "    y_true1, y_pred1 = remove_o_tags(y_true, y_pred)\n",
    "    res = pd.DataFrame.from_dict(classification_report(y_true1, y_pred1, output_dict=True, zero_division=0)).reset_index()\n",
    "    temp = res['index']\n",
    "    res.drop('index',axis=1,inplace=True)\n",
    "    res.insert(loc=0, column='split', value=split_name)\n",
    "    res.insert(loc=1, column='index', value=temp)\n",
    "    res_mostfreq = pd.concat([res_mostfreq, res],ignore_index=True)\n",
    "\n",
    "if 'O' in res_random.columns:\n",
    "    res_random.drop('O',axis=1,inplace=True)\n",
    "if 'O' in res_mostfreq.columns:\n",
    "    res_mostfreq.drop('O',axis=1,inplace=True)\n",
    "\n",
    "res_random = res_random.iloc[:, :res_random.columns.get_loc('weighted avg')+1]\n",
    "res_mostfreq = res_mostfreq.iloc[:, :res_mostfreq.columns.get_loc('weighted avg')+1]\n",
    "\n",
    "res_random.to_csv('baseline_meddra_model'+suf+'/random_classification_report.csv',index=False)\n",
    "res_mostfreq.to_csv('baseline_meddra_model'+suf+'/mostfreq_classification_report.csv',index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['split',\n",
       " 'index',\n",
       " 'B-Lipitor',\n",
       " 'I-CONCEPT_LESS',\n",
       " 'I-Severe_pain',\n",
       " 'B-CONCEPT_LESS',\n",
       " 'I-Myalgia',\n",
       " 'B-Pain',\n",
       " 'B-Myalgia',\n",
       " 'I-Muscle_weakness',\n",
       " 'B-Severe_pain',\n",
       " 'I-Arthralgia',\n",
       " 'I-Walking_disability',\n",
       " 'I-Cramp_in_lower_limb',\n",
       " 'I-Pain_in_lower_limb',\n",
       " 'I-Hip_pain',\n",
       " 'B-Fatigue',\n",
       " 'B-Arthralgia',\n",
       " 'B-Muscle_cramp',\n",
       " 'I-Shoulder_pain',\n",
       " 'I-Pins_and_needles',\n",
       " 'I-Foot_pain',\n",
       " 'I-Backache',\n",
       " 'I-Weakness_of_limb',\n",
       " 'B-Depression',\n",
       " 'I-Knee_pain',\n",
       " 'I-Poor_short-term_memory',\n",
       " 'B-Excessive_upper_gastrointestinal_gas',\n",
       " 'B-Headache',\n",
       " 'I-Excessive_upper_gastrointestinal_gas',\n",
       " 'I-Neck_pain',\n",
       " 'B-Asthenia',\n",
       " 'I-Generalised_aches_and_pains',\n",
       " 'I-Muscle_atrophy',\n",
       " 'I-Stomach_ache',\n",
       " 'I-Mentally_dull',\n",
       " 'I-Muscle_cramp',\n",
       " 'B-Cramp_in_lower_limb',\n",
       " 'B-Backache',\n",
       " 'I-Low_back_pain',\n",
       " 'I-Amnesia',\n",
       " 'I-Influenza-like_illness',\n",
       " 'B-Diarrhoea',\n",
       " 'B-Muscle_weakness',\n",
       " 'B-Amnesia',\n",
       " 'B-Pain_in_lower_limb',\n",
       " 'I-Unable_to_walk',\n",
       " 'B-Hip_pain',\n",
       " 'I-Pain_in_calf',\n",
       " 'B-Dizziness',\n",
       " 'B-Walking_disability',\n",
       " 'I-Myalgia/myositis_-_lower_leg',\n",
       " 'I-Unable_to_get_off_a_bed',\n",
       " 'B-Nausea',\n",
       " 'B-Knee_pain',\n",
       " 'I-Rash',\n",
       " 'B-Shoulder_pain',\n",
       " 'I-Memory_impairment',\n",
       " 'B-Insomnia',\n",
       " 'I-Lightheadedness',\n",
       " 'B-Stomach_ache',\n",
       " 'B-Pins_and_needles',\n",
       " 'I-Pain_in_upper_limb',\n",
       " 'B-Arthrotec',\n",
       " 'I-Flushing',\n",
       " 'I-Headache',\n",
       " 'B-Arthritis',\n",
       " 'B-Foot_pain',\n",
       " 'I-Charleyhorse',\n",
       " 'B-Neck_pain',\n",
       " 'I-Muscle_fatigue',\n",
       " 'I-Numbness_of_lower_limb',\n",
       " 'I-Asthenia',\n",
       " 'I-Reduced_libido',\n",
       " 'I-Loss_of_hair',\n",
       " 'I-Difficulty_sleeping',\n",
       " 'I-Visual_disturbance',\n",
       " 'I-Myocardial_infarction',\n",
       " 'I-Blurred_vision_-_hazy',\n",
       " 'I-Loss_of_motivation',\n",
       " 'I-Unable_to_concentrate',\n",
       " 'I-Pain_provoked_by_movement',\n",
       " 'B-Zocor',\n",
       " 'I-Stomach_cramps',\n",
       " 'B-Myocardial_infarction',\n",
       " 'I-Thigh_pain',\n",
       " 'I-Fatigue',\n",
       " 'I-Ankle_pain',\n",
       " 'I-Tired',\n",
       " 'B-Loss_of_hair',\n",
       " 'I-Myopathy',\n",
       " 'I-Upset_stomach',\n",
       " 'B-Weakness_of_limb',\n",
       " 'B-ubidecarenone',\n",
       " 'I-Myalgia/myositis_-_shoulder',\n",
       " 'B-Bloating_symptom',\n",
       " 'B-Tired',\n",
       " 'I-Lack_of_energy',\n",
       " 'I-Cramp_in_calf',\n",
       " 'I-Impairment_of_balance',\n",
       " 'I-Cannot_sleep_at_all',\n",
       " 'I-Acid_reflux',\n",
       " 'I-Dyspnoea',\n",
       " 'B-Blurred_vision_-_hazy',\n",
       " 'I-Chest_pain',\n",
       " 'I-Pain',\n",
       " 'B-Mentally_dull',\n",
       " 'B-Muscle_atrophy',\n",
       " 'I-Burning_feet',\n",
       " 'I-Bleeding_between_periods',\n",
       " 'I-Restless_legs',\n",
       " 'B-Generalised_aches_and_pains',\n",
       " 'I-Weight_gain',\n",
       " 'B-Poor_short-term_memory',\n",
       " 'I-Tired_all_the_time',\n",
       " 'I-Abdominal_pain',\n",
       " 'I-Difficulty_walking_up_stairs',\n",
       " 'B-Rash',\n",
       " 'I-Muscle_twitch',\n",
       " 'I-Serum_cholesterol_raised',\n",
       " 'I-Unable_to_climb_stairs',\n",
       " 'B-Low_back_pain',\n",
       " 'I-Sensation_of_hot_and_cold',\n",
       " 'I-Generalised_acute_body_pains',\n",
       " 'B-Constipation',\n",
       " 'B-Anxiety',\n",
       " 'I-Unable_to_think_clearly',\n",
       " 'B-Memory_impairment',\n",
       " 'I-Cramp_in_foot',\n",
       " 'B-Vertigo',\n",
       " 'B-Chest_pain',\n",
       " 'I-Thoracic_back_pain',\n",
       " 'I-Paraesthesia_of_lower_extremity',\n",
       " 'B-Stomach_cramps',\n",
       " 'B-Voltaren',\n",
       " 'I-Finding_of_increased_blood_pressure',\n",
       " 'I-Unable_to_walk_up_step',\n",
       " 'B-Pravachol',\n",
       " 'I-Liver_enzymes_abnormal',\n",
       " 'B-Myopathy',\n",
       " 'I-Rupture_of_Achilles_tendon',\n",
       " 'I-Myalgia/myositis_-pelvis/thigh',\n",
       " 'I-Stiff_legs',\n",
       " 'I-Burning_pain',\n",
       " 'I-Hypersomnia',\n",
       " 'I-Pulse_fast',\n",
       " 'B-Unable_to_walk',\n",
       " 'B-Influenza-like_illness',\n",
       " 'B-Numbness',\n",
       " 'I-Unable_to_move_arm',\n",
       " 'I-Myalgia/myositis_-_multiple',\n",
       " 'B-Difficulty_sleeping',\n",
       " 'B-Upset_stomach',\n",
       " 'I-Burning_sensation',\n",
       " 'I-Heart_disease',\n",
       " 'B-Lightheadedness',\n",
       " 'B-Cannot_sleep_at_all',\n",
       " 'B-Flatulence/wind',\n",
       " 'B-Bleeding',\n",
       " 'B-Abdominal_pain',\n",
       " 'I-Tight_chest',\n",
       " 'I-Myalgia/myositis_-_forearm',\n",
       " 'B-Itching',\n",
       " 'I-Postmenopausal_bleeding',\n",
       " 'I-Stabbing_pain',\n",
       " 'I-Arthritis_of_hand',\n",
       " 'B-Visual_disturbance',\n",
       " 'I-Plantar_fasciitis',\n",
       " 'B-Pain_in_calf',\n",
       " 'B-Weight_gain',\n",
       " 'I-Generally_unwell',\n",
       " 'I-Hand_pain',\n",
       " 'I-Muscle_tension',\n",
       " 'I-Uterine_spasm',\n",
       " 'I-Pain_in_elbow',\n",
       " 'I-Spasm_of_back_muscles',\n",
       " 'B-Increased_cholesterol_esters',\n",
       " 'I-Increased_cholesterol_esters',\n",
       " 'B-Heart_disease',\n",
       " 'B-Feeling_irritable',\n",
       " 'B-Lack_of_energy',\n",
       " 'B-Stiffness',\n",
       " 'I-Constant_pain',\n",
       " 'I-Pain_provoked_by_walking',\n",
       " 'I-Limitation_of_joint_movement',\n",
       " 'I-Random_blood_sugar_raised',\n",
       " 'I-Tachycardia',\n",
       " 'I-Intercostal_myalgia',\n",
       " 'I-Liver_disease',\n",
       " 'I-Irregular_menstruation',\n",
       " 'B-Reduced_libido',\n",
       " 'I-Failure_to_lose_weight',\n",
       " 'I-Itching_of_skin',\n",
       " 'B-Pain_in_upper_limb',\n",
       " 'I-Paraesthesia_of_hand',\n",
       " 'I-Unable_to_balance',\n",
       " 'I-Tinnitus',\n",
       " 'B-Muscle_fatigue',\n",
       " 'B-Unable_to_concentrate',\n",
       " 'B-Burning_sensation',\n",
       " 'B-Swelling',\n",
       " 'I-Menorrhagia',\n",
       " 'I-Vaginal_bleeding',\n",
       " 'I-Increased_venous_pressure',\n",
       " 'B-Crestor',\n",
       " 'I-Excruciating_pain',\n",
       " 'B-Dyspnoea',\n",
       " 'I-Difficulty_getting_off_a_bed',\n",
       " 'I-Impaired_exercise_tolerance',\n",
       " 'I-Peripheral_neuropathy',\n",
       " 'B-Tiredness_symptom',\n",
       " 'I-Numbness_of_limbs',\n",
       " 'I-Abdominal_colic',\n",
       " 'I-Serum_creatinine_raised',\n",
       " 'I-Heel_pain',\n",
       " 'B-Exhaustion',\n",
       " 'B-Myalgia/myositis_-_lower_leg',\n",
       " 'I-omega-3-acid_ethyl_esters-90',\n",
       " 'I-Foot_swelling',\n",
       " 'I-Loss_of_taste',\n",
       " 'I-Numbness_of_hand',\n",
       " 'I-Acute_pain',\n",
       " 'I-Urinary_frequency',\n",
       " 'I-Mood_swings',\n",
       " 'I-Incoordination',\n",
       " 'B-Impairment_of_balance',\n",
       " 'B-Ankle_pain',\n",
       " 'B-Diabetes_mellitus',\n",
       " 'B-ascorbic_acid',\n",
       " 'I-ascorbic_acid',\n",
       " 'B-Fibromyalgia',\n",
       " 'B-Vaginal_bleeding',\n",
       " 'I-Numbness_of_upper_limb',\n",
       " 'I-Heavy_legs',\n",
       " 'I-Sharp_pain',\n",
       " 'I-Haematochezia',\n",
       " 'I-Arthralgia_of_the_lower_leg',\n",
       " 'I-Pain_in_toe',\n",
       " 'I-Weakness_of_hand',\n",
       " 'B-ezetimibe',\n",
       " 'B-Loss_of_motivation',\n",
       " 'I-Dizziness',\n",
       " 'I-Tightness_in_throat',\n",
       " 'I-Aptyalism',\n",
       " 'I-Migraine',\n",
       " \"I-Bell's_palsy\",\n",
       " 'I-Lack_of_stamina',\n",
       " 'I-Sensation_of_heaviness_in_limbs',\n",
       " 'I-Poor_concentration',\n",
       " 'I-Facial_swelling',\n",
       " 'B-Tinnitus',\n",
       " 'I-Elbow_joint_pain',\n",
       " 'I-Malaise',\n",
       " 'I-Irritable_bowel_syndrome_characterised_by_constipation',\n",
       " 'I-Pain_in_left_arm',\n",
       " 'I-Deep_pain',\n",
       " 'I-Aphasia',\n",
       " 'I-Spasm',\n",
       " 'B-Tendonitis',\n",
       " 'B-Cramp_in_calf',\n",
       " 'B-ibuprofen',\n",
       " 'B-Muscle_twitch',\n",
       " 'B-Liver_disease',\n",
       " 'B-Amyotrophic_lateral_sclerosis',\n",
       " 'I-Derealisation',\n",
       " 'I-Myalgia/myositis_-_upper_arm',\n",
       " 'I-ubidecarenone',\n",
       " 'B-Acid_reflux',\n",
       " 'I-Joint_stiffness',\n",
       " 'B-Pain_in_elbow',\n",
       " 'I-Personality_change',\n",
       " 'I-Ringing_in_ear',\n",
       " 'I-Difficulty_breathing',\n",
       " 'I-Hand_joint_stiff',\n",
       " 'B-Vomiting',\n",
       " 'B-Spasm',\n",
       " 'B-Drowsy',\n",
       " 'B-Mood_swings',\n",
       " 'I-Dry_skin',\n",
       " 'B-Restless_legs',\n",
       " 'B-Thigh_pain',\n",
       " 'I-Body_fluid_retention',\n",
       " 'B-Migraine',\n",
       " 'I-Bleeding',\n",
       " 'I-Discolouration_of_skin',\n",
       " 'I-Vertigo',\n",
       " 'B-Tired_all_the_time',\n",
       " 'B-Palpitations',\n",
       " 'B-Tremor',\n",
       " 'B-fenofibrate',\n",
       " 'B-Indigestion',\n",
       " 'I-Hypertension',\n",
       " 'B-Confusion',\n",
       " 'I-Knee_stiff',\n",
       " 'I-Difficulty_chewing',\n",
       " 'I-Weight_increased',\n",
       " 'B-Cerebrovascular_accident',\n",
       " 'I-Flatulence,_eructation_and_gas_pain',\n",
       " 'B-Charleyhorse',\n",
       " 'I-Cramp_in_lower_leg',\n",
       " 'I-Calf_muscle_weakness',\n",
       " 'B-Unable_to_think_clearly',\n",
       " 'I-Numbness_of_foot',\n",
       " 'B-Abdominal_colic',\n",
       " 'I-Cramp_in_limb',\n",
       " 'B-Moody',\n",
       " 'I-Feeling_empty',\n",
       " 'B-Serum_creatinine_raised',\n",
       " 'I-Flatulence/wind',\n",
       " 'I-Lack_of_libido',\n",
       " 'B-Aptyalism',\n",
       " 'B-Finding_of_increased_blood_pressure',\n",
       " 'I-Spasmodic_movement',\n",
       " 'I-Loss_of_appetite',\n",
       " 'I-fish_oil_natural',\n",
       " 'I-Swollen_legs',\n",
       " 'B-Neuropathy',\n",
       " 'I-Nerve_injury',\n",
       " 'I-Haemorrhage_of_abdominal_cavity_structure',\n",
       " 'B-Malaise',\n",
       " 'I-Pain_in_left_leg',\n",
       " 'I-Lower_abdominal_pain',\n",
       " 'I-Paraesthesia_of_foot',\n",
       " 'I-Loss_of_interest',\n",
       " 'I-Swollen_ankle',\n",
       " 'I-Clicking_interphalangeal_joint_of_toe',\n",
       " 'I-Initial_insomnia',\n",
       " 'I-Malignant_neoplasm_of_brain',\n",
       " 'I-Reduced_mobility',\n",
       " 'I-Swelling_of_finger',\n",
       " 'I-Peeling_of_skin',\n",
       " 'I-Oedema_of_lower_extremity',\n",
       " 'B-Cough',\n",
       " 'B-Cramp_in_foot',\n",
       " 'B-Influenza',\n",
       " 'B-Hypertension',\n",
       " 'B-Gout',\n",
       " 'B-Hand_pain',\n",
       " 'B-Inflammatory_disorder',\n",
       " 'B-Constant_pain',\n",
       " 'B-Serum_cholesterol_raised',\n",
       " 'I-Unable_to_stand',\n",
       " 'I-Weight_loss',\n",
       " 'I-Depression',\n",
       " 'I-Renal_impairment',\n",
       " 'I-White_blood_cell_count_abnormal',\n",
       " 'I-Acenaesthesia',\n",
       " 'I-Shoulder_joint_pain',\n",
       " 'I-Pain_in_finger',\n",
       " 'I-Stiffness',\n",
       " 'B-Peripheral_neuropathy',\n",
       " 'I-Unsteady_when_standing',\n",
       " 'I-Menstrual_cramp',\n",
       " 'I-Heavy_feeling',\n",
       " 'B-Multiple_sclerosis',\n",
       " 'I-Numbness_of_face',\n",
       " 'I-Ovarian_pain',\n",
       " 'B-Celebrex',\n",
       " 'I-Oedema_of_extremity',\n",
       " 'I-Increased_liver_function',\n",
       " 'B-Tachycardia',\n",
       " 'I-Erythema_of_skin',\n",
       " 'B-Unable_to_get_off_a_bed',\n",
       " 'B-Hypersomnia',\n",
       " 'B-Plantar_fasciitis',\n",
       " 'I-alpha_tocopherol',\n",
       " 'I-Tylenol',\n",
       " 'I-Hand_cramps',\n",
       " 'B-Stiff_neck',\n",
       " 'I-Stiff_neck',\n",
       " 'B-Spasmodic_movement',\n",
       " 'I-Kidney_disease',\n",
       " 'I-Muscle_rigidity',\n",
       " 'I-Renal_pain',\n",
       " 'B-Severe_depression',\n",
       " 'I-Severe_depression',\n",
       " 'I-Suicidal_thoughts',\n",
       " 'B-Advil',\n",
       " 'B-Rheumatoid_arthritis',\n",
       " 'B-Lupus_erythematosus',\n",
       " 'B-Liver_enzymes_abnormal',\n",
       " 'B-Heel_pain',\n",
       " 'B-Poor_concentration',\n",
       " 'I-Dry_eyes',\n",
       " 'B-simvastatin',\n",
       " 'B-omega-3-acid_ethyl_esters-90',\n",
       " 'B-Joint_stiffness',\n",
       " 'B-Increased_venous_pressure',\n",
       " 'B-Aleve',\n",
       " 'B-Heartburn',\n",
       " 'B-Excruciating_pain',\n",
       " 'B-Limping',\n",
       " 'I-Limping',\n",
       " 'B-Stress',\n",
       " 'I-Feeling_faint',\n",
       " 'B-diclofenac',\n",
       " 'B-Difficulty_breathing',\n",
       " 'B-Pain_in_toe',\n",
       " 'I-Type_2_diabetes_mellitus',\n",
       " 'B-Menstrual_cramp',\n",
       " 'I-Right_hemiparesis',\n",
       " 'B-Flushing',\n",
       " 'I-Unable_to_find_words',\n",
       " 'I-Unable_to_lift',\n",
       " 'I-Tendonitis_AND/OR_tenosynovitis_of_the_elbow_region',\n",
       " 'I-Large_breast',\n",
       " 'I-Clicking_knee',\n",
       " 'I-Symptom_of_ankle',\n",
       " 'I-Increased_lactic_acid_level',\n",
       " 'I-Tremor',\n",
       " 'I-Parkinsonian_tremor',\n",
       " 'I-Abdominal_hyperaesthesia',\n",
       " 'I-Tenalgia',\n",
       " 'I-Unable_to_move_leg',\n",
       " 'B-Tylenol',\n",
       " 'B-Burning_feet',\n",
       " 'B-Kidney_disease',\n",
       " 'B-Myalgia/myositis_-_shoulder',\n",
       " 'B-Forgetful',\n",
       " 'I-Non-smoker',\n",
       " 'B-Generally_unwell',\n",
       " 'I-Rheumatoid_arthritis',\n",
       " 'I-Muscle_strain',\n",
       " 'B-Pain_provoked_by_movement',\n",
       " 'B-Itching_of_skin',\n",
       " 'I-Unsteady_when_walking',\n",
       " 'B-Lack_of_stamina',\n",
       " 'B-Loss_of_appetite',\n",
       " 'I-Serum_triglycerides_raised',\n",
       " 'B-fish_oil_natural',\n",
       " 'B-Paraesthesia_of_hand',\n",
       " 'I-Urinary_retention',\n",
       " 'I-Palpitations',\n",
       " \"I-Parkinson's_disease\",\n",
       " 'I-Difficulty_lifting',\n",
       " 'I-Gastrointestinal_tract_problem',\n",
       " 'B-Impaired_exercise_tolerance',\n",
       " 'B-Delusional_disorder',\n",
       " 'I-Nausea',\n",
       " 'B-Lethargy',\n",
       " 'I-Insomnia',\n",
       " 'B-Menopause_present',\n",
       " 'I-Itching',\n",
       " 'B-Random_blood_sugar_raised',\n",
       " 'I-Unable_to_get_out_of_a_chair',\n",
       " 'I-Confusion',\n",
       " 'I-Slurred_speech',\n",
       " 'I-Numbness',\n",
       " 'B-Illness',\n",
       " 'B-Unable_to_balance',\n",
       " 'I-Panic_attack',\n",
       " 'I-Stomach_problem',\n",
       " 'I-Dysphonia',\n",
       " 'I-Shoulder_stiff',\n",
       " 'I-Intervertebral_disc_prolapse',\n",
       " 'I-Joint_crepitus',\n",
       " 'I-Urine:_dark/concentrated',\n",
       " 'I-Blistering_rash',\n",
       " 'B-Swollen_ankle',\n",
       " 'I-Tingling_of_skin',\n",
       " 'I-Unable_to_lie_down',\n",
       " 'I-Numbness_and_tingling_sensation_of_skin',\n",
       " 'I-Discomfort',\n",
       " 'I-Coronary_arteriosclerosis',\n",
       " 'I-Hand_joint_pain',\n",
       " 'I-Tightness_sensation',\n",
       " 'B-Pulse_fast',\n",
       " 'B-Sweating',\n",
       " 'I-Glossitis',\n",
       " 'I-Stiff_limbs',\n",
       " 'I-cortisone',\n",
       " 'I-Difficulty_swallowing',\n",
       " 'I-Carpal_tunnel_syndrome',\n",
       " 'I-Arthritis',\n",
       " 'I-Myositis',\n",
       " 'B-Muscle_rigidity',\n",
       " 'B-Menorrhagia',\n",
       " 'I-Infective_cystitis',\n",
       " 'B-Lopid',\n",
       " 'I-Exhaustion',\n",
       " 'B-Unable_to_climb_stairs',\n",
       " 'B-Weight_loss',\n",
       " 'I-Rib_pain',\n",
       " 'B-Uterine_spasm',\n",
       " 'I-Cold_sweat',\n",
       " 'B-prednisone',\n",
       " 'I-Swelling_of_knee_joint',\n",
       " 'I-Swollen_knee',\n",
       " 'B-Disorientated',\n",
       " 'B-Asthma',\n",
       " 'I-Sleep_deprivation',\n",
       " 'B-Zoloft',\n",
       " 'B-Spasm_of_back_muscles',\n",
       " 'B-Nerve_injury',\n",
       " 'I-C-reactive_protein_abnormal',\n",
       " 'I-Excessive_and_frequent_menstruation',\n",
       " 'I-Increased_creatine_kinase_level',\n",
       " 'B-Slurred_speech',\n",
       " 'I-Reduction_of_bulk_of_muscle',\n",
       " 'I-Respiratory_depression',\n",
       " 'B-Panic_attack',\n",
       " 'B-Stomach_problem',\n",
       " 'B-Paraesthesia_of_lower_extremity',\n",
       " 'B-ezetimibe_+_simvastatin',\n",
       " 'I-Pain_in_wrist',\n",
       " 'I-Abdominal_wind_pain',\n",
       " 'B-Fever',\n",
       " 'B-Numbness_of_hand',\n",
       " 'I-Hypertonia',\n",
       " 'I-Decreased_cholesterol_esters',\n",
       " 'I-Impaired_mobility',\n",
       " 'I-Heartburn',\n",
       " 'B-Numbness_of_lower_limb',\n",
       " 'I-Dependance_on_walking_stick',\n",
       " 'I-Difficulty_moving_hand',\n",
       " 'I-Mucosal_numbness',\n",
       " 'I-Acne',\n",
       " 'I-Bizarre_dreams',\n",
       " 'I-Achilles_tendonitis',\n",
       " 'I-Night_pain',\n",
       " 'I-Heavy_episode_of_vaginal_bleeding',\n",
       " 'I-Diarrhoea',\n",
       " 'I-Difficulty_getting_out_of_a_chair',\n",
       " 'I-Blind_or_low_vision_-_one_eye_only',\n",
       " 'I-Always_sleepy',\n",
       " 'I-Hyperaemia_of_surface_of_eye',\n",
       " 'I-Pain_provoked_by_rest',\n",
       " 'I-Difficulty_standing',\n",
       " 'I-Abdominal_bloating',\n",
       " 'B-Dry_skin',\n",
       " 'B-Numbness_of_foot',\n",
       " 'B-cortisone',\n",
       " 'B-alpha_tocopherol',\n",
       " 'B-Difficulty_swallowing',\n",
       " 'I-Chronic_back_pain',\n",
       " 'I-Disorder_of_foot',\n",
       " 'B-Malignant_neoplastic_disease',\n",
       " 'B-Tightness_in_throat',\n",
       " 'B-Renal_pain',\n",
       " 'B-Syncope',\n",
       " 'I-Forgetful',\n",
       " 'I-Urinary_tract_infection',\n",
       " 'I-Bone_pain',\n",
       " 'I-Digestive_symptom',\n",
       " 'I-Scalp_itchy',\n",
       " \"B-Bell's_palsy\",\n",
       " 'I-Abnormal_dreams',\n",
       " 'I-Swallowing_problem',\n",
       " 'B-Muscle_tension',\n",
       " 'B-Feeling_unhappy',\n",
       " 'B-Dry_eyes',\n",
       " 'I-Arthrotec',\n",
       " 'I-Photosensitisation_due_to_sun',\n",
       " 'B-Pain_provoked_by_walking',\n",
       " 'B-Facial_swelling',\n",
       " 'I-Excessive_sweating',\n",
       " 'I-Hoarse',\n",
       " 'B-Rib_pain',\n",
       " 'I-Pounding_heart',\n",
       " 'B-Chill',\n",
       " 'B-Foot_swelling',\n",
       " 'B-Tight_chest',\n",
       " 'B-Thoracic_back_pain',\n",
       " 'B-Limitation_of_joint_movement',\n",
       " 'B-Myalgia/myositis_-_forearm',\n",
       " 'I-Lumbar_facet_joint_pain',\n",
       " 'I-Fear',\n",
       " 'B-Heavy_legs',\n",
       " 'B-Myalgia/myositis_-pelvis/thigh',\n",
       " 'B-Nasal_sinus_problem',\n",
       " 'I-Nasal_sinus_problem',\n",
       " 'B-Stiff_legs',\n",
       " 'B-Loss_of_taste',\n",
       " 'I-Urine_looks_dark',\n",
       " 'B-Pain_in_finger',\n",
       " 'B-Knee_stiff',\n",
       " 'I-Hip_stiff',\n",
       " 'B-Discomfort',\n",
       " 'I-Slow_on_legs',\n",
       " 'B-Pain_in_throat',\n",
       " 'I-Pain_in_throat',\n",
       " 'I-Unable_to_eat',\n",
       " 'B-Pain_in_wrist',\n",
       " 'B-Weight_increased',\n",
       " 'I-Bipolar_disorder',\n",
       " 'I-Low_blood_pressure_reading',\n",
       " 'I-Gastric_ulcer',\n",
       " 'I-Fine_motor_impairment',\n",
       " 'I-Lateral_epicondylitis',\n",
       " 'I-Arthritis_of_knee',\n",
       " 'I-Arthritis_of_hip',\n",
       " 'B-Stabbing_pain',\n",
       " 'B-Type_2_diabetes_mellitus',\n",
       " 'I-Chronic_fatigue_syndrome',\n",
       " 'I-Middle_insomnia',\n",
       " 'I-Swollen_nasal_mucosa',\n",
       " 'I-Yellow_skin',\n",
       " 'B-Cramp_in_lower_leg',\n",
       " 'I-Arthralgia_of_multiple_joints',\n",
       " 'I-Wrist_joint_pain',\n",
       " 'B-Bizarre_dreams',\n",
       " 'I-Shoulder_tendonitis',\n",
       " 'I-Pancreatitis',\n",
       " 'I-Rupture_of_tendon_of_lower_leg_and_ankle',\n",
       " 'I-Hyperaesthesia',\n",
       " 'I-Impaired_bed_mobility',\n",
       " 'I-Musculoskeletal_pain',\n",
       " 'B-Norvasc',\n",
       " 'I-Unable_to_speak',\n",
       " 'I-Unable_to_move_all_four_limbs',\n",
       " 'I-Strain_of_calf_muscle',\n",
       " 'I-Difficulty_dressing',\n",
       " 'I-Feels_everything_is_futile',\n",
       " 'B-Reduced_mobility',\n",
       " 'B-Difficulty_walking_up_stairs',\n",
       " 'B-Abdominal_bloating',\n",
       " 'B-Eczema',\n",
       " 'B-Swelling_of_finger',\n",
       " 'I-Propensity_to_adverse_reactions_to_drug',\n",
       " 'I-Unable_to_walk_down_stairs',\n",
       " 'B-Hand_cramps',\n",
       " 'B-Carpal_tunnel_syndrome',\n",
       " 'B-aspirin',\n",
       " 'B-Rhabdomyolysis',\n",
       " 'B-Infective_cystitis',\n",
       " 'B-Lack_of_libido',\n",
       " 'B-Nightmares',\n",
       " 'I-Hepatic_trauma',\n",
       " 'B-Diovan',\n",
       " 'B-Haematuria',\n",
       " 'B-Suicidal_thoughts',\n",
       " 'B-Muscle_strain',\n",
       " 'I-Type_1_diabetes_mellitus',\n",
       " 'B-Steatosis_of_liver',\n",
       " 'I-Steatosis_of_liver',\n",
       " 'B-Disorder_of_muscle',\n",
       " 'B-Sensation_of_heaviness_in_limbs',\n",
       " 'B-Abnormal_dreams',\n",
       " 'B-Swallowing_problem',\n",
       " 'I-Right_upper_quadrant_pain',\n",
       " 'I-Liver_function_tests_abnormal',\n",
       " 'I-Gallbladder_disorder',\n",
       " 'I-Rupture_of_tendon',\n",
       " 'B-Photosensitisation_due_to_sun',\n",
       " 'I-Deteriorating_renal_function',\n",
       " 'I-Pain_in_thumb',\n",
       " 'I-Burning_sensation_of_vagina',\n",
       " 'B-Excessive_sweating',\n",
       " 'B-Cramp',\n",
       " 'I-Cramp',\n",
       " 'B-Swollen_legs',\n",
       " \"B-Parkinson's_disease\",\n",
       " 'I-Neuroma_of_foot',\n",
       " 'B-Swollen_knee',\n",
       " 'I-Neuropathy_of_upper_limb',\n",
       " 'I-Swelling_of_hand',\n",
       " 'B-Numbness_of_upper_limb',\n",
       " 'I-Ankle_oedema',\n",
       " 'I-Urinary_incontinence',\n",
       " 'B-Sciatica',\n",
       " 'I-Disorder_of_nasal_sinus',\n",
       " 'I-Pain_in_limb',\n",
       " 'B-Elbow_joint_pain',\n",
       " 'B-Ringing_in_ear',\n",
       " 'B-Increased_creatine_kinase_level',\n",
       " 'I-Tendonitis',\n",
       " 'B-Bronchitis',\n",
       " 'B-Urine_looks_dark',\n",
       " 'I-Frequent_defaecation',\n",
       " 'B-Hunger_pain',\n",
       " 'I-Hunger_pain',\n",
       " 'I-Unable_to_stand_up',\n",
       " 'B-Generalised_acute_body_pains',\n",
       " 'B-atorvastatin',\n",
       " 'B-Haematochezia',\n",
       " 'B-Dysphonia',\n",
       " 'I-Ulcer_of_oesophagus',\n",
       " 'I-Neuropathy',\n",
       " 'B-Intervertebral_disc_prolapse',\n",
       " 'B-Respiratory_tract_congestion',\n",
       " 'B-Arthralgia_of_the_lower_leg',\n",
       " 'B-Hand_joint_stiff',\n",
       " 'I-Neuropathy_of_lower_limb',\n",
       " 'I-Oedema_of_finger',\n",
       " 'B-Menstrual_spotting',\n",
       " 'B-Gastric_ulcer',\n",
       " 'I-Joint_laxity',\n",
       " 'I-Lacks_confidence',\n",
       " 'I-Type_II_diabetes_mellitus_uncontrolled',\n",
       " 'I-Gastrointestinal_symptom',\n",
       " 'B-Flatulence,_eructation_and_gas_pain',\n",
       " 'I-Feeling_irritable',\n",
       " 'I-Influenza-like_symptoms',\n",
       " 'I-Increased_thirst',\n",
       " 'B-Reflux',\n",
       " 'I-Muscle_spasms_of_head_AND/OR_neck',\n",
       " 'B-Unable_to_move_arm',\n",
       " 'I-Unable_to_move',\n",
       " 'I-Decreased_muscle_tone',\n",
       " 'I-Loss_of_confidence',\n",
       " 'I-Contusion_of_hand',\n",
       " 'I-Chill',\n",
       " 'I-Pain_in_right_arm',\n",
       " 'I-Irregular_heart_beat',\n",
       " 'I-Muscle_injury',\n",
       " 'I-Warm_hands',\n",
       " 'I-Compression_neuropathy_of_trunk',\n",
       " 'I-Muscle_fasciculation',\n",
       " 'I-Intolerant_of_cold',\n",
       " 'B-Malignant_neoplasm_of_brain',\n",
       " 'I-Haematuria',\n",
       " 'I-Knee_joint_painful_on_movement',\n",
       " 'B-Acute_pain',\n",
       " 'I-Numbness_of_toe',\n",
       " 'B-paracetamol',\n",
       " 'I-Ankle_joint_pain',\n",
       " 'I-Unable_to_move_hand',\n",
       " 'I-Iliotibial_band_friction_syndrome',\n",
       " 'I-Malaise_and_fatigue',\n",
       " 'I-Diastolic_dysfunction',\n",
       " 'I-Right_ventricular_dilatation',\n",
       " 'I-Abdominal_distension',\n",
       " 'I-Pain_in_cheek',\n",
       " 'I-Skin_nodule',\n",
       " 'B-Loose_stool',\n",
       " 'I-Loose_stool',\n",
       " 'B-Peeling_of_skin',\n",
       " 'B-Incoordination',\n",
       " 'B-Numbness_of_limbs',\n",
       " 'B-Stiff_limbs',\n",
       " 'B-Myositis',\n",
       " 'B-Disorder_of_foot',\n",
       " 'B-Cramp_in_limb',\n",
       " 'I-Moody',\n",
       " 'B-Increased_appetite',\n",
       " 'I-Increased_appetite',\n",
       " 'B-Feeling_empty',\n",
       " 'B-glucosamine',\n",
       " 'B-Irregular_menstruation',\n",
       " 'I-Nonspecific_abdominal_symptom',\n",
       " 'I-Chronic_intractable_pain',\n",
       " 'B-metoprolol',\n",
       " 'B-Body_fluid_retention',\n",
       " 'I-Collapse',\n",
       " 'B-Blister',\n",
       " 'I-Urgent_desire_to_urinate',\n",
       " 'B-Bone_pain',\n",
       " 'B-Digestive_symptom',\n",
       " 'B-Scalp_itchy',\n",
       " 'I-Lip_swelling',\n",
       " 'I-Unable_to_make_a_fist',\n",
       " 'B-Myalgia/myositis_-_upper_arm',\n",
       " 'I-Impairment_level_of_vision',\n",
       " 'B-Serum_triglycerides_raised',\n",
       " 'I-Cardiomyopathy',\n",
       " 'B-Lipex',\n",
       " 'I-Cut_of_hand',\n",
       " 'B-Hoarse',\n",
       " 'I-Lipitor_40_mg_tablet:_film-coated',\n",
       " 'B-misoprostol',\n",
       " 'B-Cold_sweat',\n",
       " 'B-Renal_impairment',\n",
       " 'B-Neurontin',\n",
       " 'I-Bad_taste_in_mouth',\n",
       " 'I-Lopid',\n",
       " 'I-Tendonitis_of_knee',\n",
       " 'B-Swelling_of_knee_joint',\n",
       " 'B-Difficulty_getting_off_a_bed',\n",
       " 'I-Drinks_wine',\n",
       " 'B-Taste_sense_altered',\n",
       " 'I-Taste_sense_altered',\n",
       " 'B-Personality_change',\n",
       " 'B-Sleep_deprivation',\n",
       " 'B-Lipidil',\n",
       " 'I-Menstrual_loss_increasing',\n",
       " 'B-Shoulder_joint_pain',\n",
       " 'B-Sensation_of_hot_and_cold',\n",
       " 'I-Pain_in_spine',\n",
       " 'I-Bursitis_of_hip',\n",
       " 'B-Endometriosis',\n",
       " 'B-Aphasia',\n",
       " 'I-Spots_on_skin',\n",
       " 'I-Visual_impairment',\n",
       " 'I-Sacroiliac_joint_stiff',\n",
       " 'I-Sense_of_smell_impaired',\n",
       " 'B-Renal_failure',\n",
       " 'I-Renal_failure',\n",
       " 'B-Bleeding_between_periods',\n",
       " 'B-Sharp_pain',\n",
       " 'I-Cough',\n",
       " 'B-Disorder_of_eye',\n",
       " 'I-Disorder_of_eye',\n",
       " 'I-paracetamol_+_codeine',\n",
       " 'I-Fear_of_falling',\n",
       " 'I-Clammy_skin',\n",
       " 'B-Hungry',\n",
       " 'I-Loss_of_voice',\n",
       " 'B-Choking',\n",
       " 'I-Tinea_pedis',\n",
       " 'B-Rectal_haemorrhage',\n",
       " 'I-Rectal_haemorrhage',\n",
       " 'B-Colitis',\n",
       " 'B-Burning_pain',\n",
       " 'I-Cold_foot',\n",
       " 'B-Hot_sweats',\n",
       " 'B-Feeling_agitated',\n",
       " 'B-Sinusitis',\n",
       " 'I-Sinusitis',\n",
       " 'I-Respiratory_tract_congestion',\n",
       " 'I-Problem_of_visual_accommodation',\n",
       " 'I-Arthralgia_of_the_upper_arm',\n",
       " 'I-Burning_epigastric_pain',\n",
       " 'I-Constantly_crying',\n",
       " 'B-Bipolar_disorder',\n",
       " 'B-Osteoarthritis',\n",
       " 'I-Rupture_of_muscle',\n",
       " 'B-Low_blood_pressure_reading',\n",
       " 'B-Overweight',\n",
       " 'B-Raised_low_density_lipoprotein_cholesterol',\n",
       " 'I-Raised_low_density_lipoprotein_cholesterol',\n",
       " 'B-potassium',\n",
       " 'B-Always_hungry',\n",
       " 'I-Always_hungry',\n",
       " 'I-Moderate_anxiety',\n",
       " 'B-Lateral_epicondylitis',\n",
       " 'B-Hypertonia',\n",
       " 'B-Infection',\n",
       " 'B-morphine',\n",
       " 'B-Chronic_fatigue_syndrome',\n",
       " 'I-Impaired_cognition',\n",
       " 'I-Buzzing_in_ear',\n",
       " 'I-Infectious_disease_of_lung',\n",
       " 'I-Cervical_arthritis',\n",
       " 'I-Furuncle',\n",
       " 'B-Lower_abdominal_pain',\n",
       " 'B-Irritable_bowel_syndrome',\n",
       " 'B-Numbness_of_face',\n",
       " 'B-Urine:_dark/concentrated',\n",
       " 'I-Disorientated',\n",
       " 'B-Loss_of_interest',\n",
       " 'I-Pressure',\n",
       " 'B-Weakness_of_hand',\n",
       " 'I-Feeling_tired',\n",
       " 'I-Facial_spasm',\n",
       " 'I-Pain_in_pelvis',\n",
       " 'I-Cerebrovascular_accident',\n",
       " 'I-Tightness_in_arm',\n",
       " 'B-Tingling_of_skin',\n",
       " 'I-Elevated_cholesterol/high_density_lipoprotein_ratio',\n",
       " 'I-Disorder_of_face',\n",
       " 'B-Achilles_tendonitis',\n",
       " 'B-Arthritis_of_hand',\n",
       " 'I-Abnormal_gait',\n",
       " 'B-codeine',\n",
       " 'B-Increased_liver_function',\n",
       " 'B-Pancreatitis',\n",
       " 'B-Initial_insomnia',\n",
       " 'I-Thoughts_of_self_harm',\n",
       " 'I-Heavy_feeling_in_eyelids',\n",
       " 'B-Numbness_and_tingling_sensation_of_skin',\n",
       " 'I-High_pain_threshold',\n",
       " 'I-Feeling_unhappy',\n",
       " 'B-Unable_to_walk_up_step',\n",
       " 'B-Irregular_heart_beat',\n",
       " 'I-Blood_coagulation_disorder',\n",
       " 'B-Facial_palsy',\n",
       " 'I-Facial_palsy',\n",
       " 'I-Tear_of_meniscus_of_knee',\n",
       " 'I-Sight_deteriorating',\n",
       " 'I-Skin_tenderness',\n",
       " 'I-Crying',\n",
       " 'I-Decreased_venous_pressure',\n",
       " 'I-Asthma',\n",
       " 'I-Disturbance_in_physical_behaviour',\n",
       " 'I-Unable_to_feed_self',\n",
       " 'B-Coronary_arteriosclerosis',\n",
       " 'I-Sudden_visual_loss',\n",
       " 'I-Difficulty_writing',\n",
       " 'I-Parkinsonism',\n",
       " 'B-Herpes_zoster',\n",
       " 'I-Weakness_of_back',\n",
       " 'I-Paraesthesia',\n",
       " 'I-Swollen_feet',\n",
       " 'I-Musculoskeletal_chest_pain',\n",
       " 'I-Viral_upper_respiratory_tract_infection',\n",
       " 'B-Bursitis',\n",
       " 'I-Arthritis/arthrosis',\n",
       " 'I-Shin_splint',\n",
       " 'I-Disorder_of_cardiac_function',\n",
       " 'I-Difficulty_gripping',\n",
       " 'I-Difficulty_moving_arm',\n",
       " 'I-Prolonged_periods',\n",
       " 'I-Not_getting_enough_sleep',\n",
       " 'I-White_discolouration_of_skin',\n",
       " 'I-Traumatic_blister_of_mouth',\n",
       " 'I-Pain_of_uterus',\n",
       " 'I-Morbid_thoughts',\n",
       " 'B-Erythema_of_skin',\n",
       " 'I-Abnormal_liver_function',\n",
       " 'B-Oedema_of_lower_extremity',\n",
       " 'B-Unable_to_move_leg',\n",
       " 'B-Chronic_back_pain',\n",
       " 'B-Intercostal_myalgia',\n",
       " 'I-Influenza',\n",
       " 'I-Contracture_of_tendon_of_ankle_region',\n",
       " 'B-Nonspecific_abdominal_symptom',\n",
       " 'B-Chest_discomfort',\n",
       " 'I-Chest_discomfort',\n",
       " 'B-Blackout',\n",
       " 'B-Clumsiness',\n",
       " 'B-Hepatic_trauma',\n",
       " 'B-Zestril',\n",
       " 'B-Urinary_tract_infection',\n",
       " 'B-Non-smoker',\n",
       " 'I-Parvovirus_infection',\n",
       " 'B-Failure_to_lose_weight',\n",
       " 'B-Type_1_diabetes_mellitus',\n",
       " 'I-Orchidodynia',\n",
       " 'B-Derealisation',\n",
       " 'B-Allergic_reaction',\n",
       " 'I-Allergic_reaction',\n",
       " 'B-Discolouration_of_skin',\n",
       " 'I-Morning_stiffness_-_joint',\n",
       " 'I-Disorder_of_muscle',\n",
       " 'B-Unsteady_when_walking',\n",
       " 'I-Abnormal_muscle_function',\n",
       " 'I-Blepharospasm',\n",
       " 'B-Jaundice',\n",
       " 'B-Gallbladder_disorder',\n",
       " 'I-Disorder_of_extremity',\n",
       " 'B-soy_lecithin',\n",
       " 'B-Rupture_of_tendon',\n",
       " 'B-Rupture_of_Achilles_tendon',\n",
       " 'B-Unable_to_stand',\n",
       " 'B-Feels_hot',\n",
       " 'I-Feels_hot',\n",
       " 'I-Arthropathy_of_knee_joint',\n",
       " 'I-Reduced_concentration',\n",
       " 'B-Pain_in_thumb',\n",
       " 'I-Heart_failure',\n",
       " 'I-Degenerative_disorder_of_muscle',\n",
       " 'B-Burning_sensation_of_vagina',\n",
       " 'B-Mastalgia',\n",
       " 'I-Mastalgia',\n",
       " 'B-Erythema',\n",
       " 'B-Lipitor_40_mg_tablet:_film-coated',\n",
       " 'B-Urinary_retention',\n",
       " 'I-Amyotrophic_lateral_sclerosis',\n",
       " 'B-Feeling_intoxicated',\n",
       " 'B-Difficulty_lifting',\n",
       " 'B-Hammer_toe',\n",
       " 'I-Hammer_toe',\n",
       " 'B-White_blood_cell_count_abnormal',\n",
       " 'I-Toe_swelling',\n",
       " 'B-Injury_of_muscle',\n",
       " 'I-Injury_of_muscle',\n",
       " 'B-Swelling_of_hand',\n",
       " 'I-Daily_headache',\n",
       " 'B-Hives',\n",
       " 'I-Congestion_of_throat',\n",
       " 'I-Rapid_shallow_breathing',\n",
       " 'B-Erectile_dysfunction',\n",
       " 'B-Allergic_condition',\n",
       " 'B-General_unsteadiness',\n",
       " 'I-General_unsteadiness',\n",
       " 'I-Decreased_range_of_shoulder_movement',\n",
       " 'B-Ankle_oedema',\n",
       " \"B-Alzheimer's_disease\",\n",
       " \"I-Alzheimer's_disease\",\n",
       " 'I-Voltaren',\n",
       " 'I-Ulceration_of_colon',\n",
       " 'B-Urinary_incontinence',\n",
       " 'B-Major_depressive_disorder',\n",
       " 'I-Major_depressive_disorder',\n",
       " 'I-Proximal_interphalangeal_joint_of_finger_pain',\n",
       " 'I-Rupture_tendon_thigh',\n",
       " 'B-Fear',\n",
       " 'B-Common_cold',\n",
       " 'I-Swelling_of_lower_limb',\n",
       " 'B-Haemorrhoids',\n",
       " 'B-C-reactive_protein_abnormal',\n",
       " 'I-Upper_respiratory_tract_infection',\n",
       " 'B-Visual_impairment',\n",
       " 'I-Fragile_self-esteem',\n",
       " 'I-Immunosuppression',\n",
       " 'I-Dysfunctional_uterine_bleeding',\n",
       " 'I-Decreased_progesterone_level',\n",
       " 'B-Anaemia',\n",
       " 'I-Autoimmune_disease',\n",
       " 'B-Frequent_defaecation',\n",
       " 'I-Impending_shock',\n",
       " 'B-Lipitor_20_mg_tablet:_film-coated',\n",
       " 'I-Lipitor_20_mg_tablet:_film-coated',\n",
       " 'B-Hip_stiff',\n",
       " 'B-Postmenopausal_bleeding',\n",
       " 'B-oestradiol',\n",
       " 'B-Slow_on_legs',\n",
       " 'B-paracetamol_+_codeine',\n",
       " 'B-Clammy_skin',\n",
       " 'I-Choking',\n",
       " ...]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(res_random.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>split</th>\n",
       "      <th>index</th>\n",
       "      <th>B-Lipitor</th>\n",
       "      <th>I-CONCEPT_LESS</th>\n",
       "      <th>I-Severe_pain</th>\n",
       "      <th>B-CONCEPT_LESS</th>\n",
       "      <th>I-Myalgia</th>\n",
       "      <th>B-Pain</th>\n",
       "      <th>B-Myalgia</th>\n",
       "      <th>I-Muscle_weakness</th>\n",
       "      <th>...</th>\n",
       "      <th>B-Feeling_hopeless</th>\n",
       "      <th>B-Feeling_lonely</th>\n",
       "      <th>B-Poor_self-image</th>\n",
       "      <th>I-Poor_self-image</th>\n",
       "      <th>B-Morbid_thoughts</th>\n",
       "      <th>B-Feels_everything_is_futile</th>\n",
       "      <th>B-Transient_global_amnesia</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>macro avg</th>\n",
       "      <th>weighted avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>train</td>\n",
       "      <td>precision</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.018868</td>\n",
       "      <td>0.018182</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000565</td>\n",
       "      <td>5.791978e-04</td>\n",
       "      <td>0.671798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>train</td>\n",
       "      <td>recall</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001340</td>\n",
       "      <td>0.002353</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000565</td>\n",
       "      <td>5.525076e-04</td>\n",
       "      <td>0.000565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>train</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.002503</td>\n",
       "      <td>0.004167</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000565</td>\n",
       "      <td>1.421311e-04</td>\n",
       "      <td>0.000988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>train</td>\n",
       "      <td>support</td>\n",
       "      <td>825.0</td>\n",
       "      <td>746.000000</td>\n",
       "      <td>425.000000</td>\n",
       "      <td>351.0</td>\n",
       "      <td>296.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.000565</td>\n",
       "      <td>9.551500e+04</td>\n",
       "      <td>95515.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>dev</td>\n",
       "      <td>precision</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000544</td>\n",
       "      <td>5.479452e-04</td>\n",
       "      <td>0.832478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>dev</td>\n",
       "      <td>recall</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000544</td>\n",
       "      <td>3.581676e-07</td>\n",
       "      <td>0.000544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>dev</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000544</td>\n",
       "      <td>7.158672e-07</td>\n",
       "      <td>0.001088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>dev</td>\n",
       "      <td>support</td>\n",
       "      <td>121.0</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>44.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000544</td>\n",
       "      <td>1.286400e+04</td>\n",
       "      <td>12864.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>test</td>\n",
       "      <td>precision</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000502</td>\n",
       "      <td>4.650802e-04</td>\n",
       "      <td>0.706418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>test</td>\n",
       "      <td>recall</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000502</td>\n",
       "      <td>3.306146e-07</td>\n",
       "      <td>0.000502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>test</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000502</td>\n",
       "      <td>6.607594e-07</td>\n",
       "      <td>0.001004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>test</td>\n",
       "      <td>support</td>\n",
       "      <td>127.0</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>49.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000502</td>\n",
       "      <td>1.194800e+04</td>\n",
       "      <td>11948.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 1753 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    split      index  B-Lipitor  I-CONCEPT_LESS  I-Severe_pain   \n",
       "0   train  precision        0.0        0.018868       0.018182  \\\n",
       "1   train     recall        0.0        0.001340       0.002353   \n",
       "2   train   f1-score        0.0        0.002503       0.004167   \n",
       "3   train    support      825.0      746.000000     425.000000   \n",
       "4     dev  precision        0.0        0.000000       0.000000   \n",
       "5     dev     recall        0.0        0.000000       0.000000   \n",
       "6     dev   f1-score        0.0        0.000000       0.000000   \n",
       "7     dev    support      121.0       96.000000      36.000000   \n",
       "8    test  precision        0.0        0.000000       0.000000   \n",
       "9    test     recall        0.0        0.000000       0.000000   \n",
       "10   test   f1-score        0.0        0.000000       0.000000   \n",
       "11   test    support      127.0       86.000000      39.000000   \n",
       "\n",
       "    B-CONCEPT_LESS  I-Myalgia  B-Pain  B-Myalgia  I-Muscle_weakness  ...   \n",
       "0              0.0        0.0     0.0        0.0                0.0  ...  \\\n",
       "1              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "2              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "3            351.0      296.0   290.0      210.0              152.0  ...   \n",
       "4              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "5              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "6              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "7             44.0       33.0    46.0       26.0               21.0  ...   \n",
       "8              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "9              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "10             0.0        0.0     0.0        0.0                0.0  ...   \n",
       "11            49.0       29.0    35.0       25.0                6.0  ...   \n",
       "\n",
       "    B-Feeling_hopeless  B-Feeling_lonely  B-Poor_self-image   \n",
       "0                  0.0               0.0                0.0  \\\n",
       "1                  0.0               0.0                0.0   \n",
       "2                  0.0               0.0                0.0   \n",
       "3                  1.0               1.0                1.0   \n",
       "4                  0.0               0.0                0.0   \n",
       "5                  0.0               0.0                0.0   \n",
       "6                  0.0               0.0                0.0   \n",
       "7                  0.0               0.0                0.0   \n",
       "8                  0.0               0.0                0.0   \n",
       "9                  0.0               0.0                0.0   \n",
       "10                 0.0               0.0                0.0   \n",
       "11                 0.0               0.0                0.0   \n",
       "\n",
       "    I-Poor_self-image  B-Morbid_thoughts  B-Feels_everything_is_futile   \n",
       "0                 0.0                0.0                           0.0  \\\n",
       "1                 0.0                0.0                           0.0   \n",
       "2                 0.0                0.0                           0.0   \n",
       "3                 1.0                1.0                           1.0   \n",
       "4                 0.0                0.0                           0.0   \n",
       "5                 0.0                0.0                           0.0   \n",
       "6                 0.0                0.0                           0.0   \n",
       "7                 0.0                0.0                           0.0   \n",
       "8                 0.0                0.0                           0.0   \n",
       "9                 0.0                0.0                           0.0   \n",
       "10                0.0                0.0                           0.0   \n",
       "11                0.0                0.0                           0.0   \n",
       "\n",
       "    B-Transient_global_amnesia  accuracy     macro avg  weighted avg  \n",
       "0                          0.0  0.000565  5.791978e-04      0.671798  \n",
       "1                          0.0  0.000565  5.525076e-04      0.000565  \n",
       "2                          0.0  0.000565  1.421311e-04      0.000988  \n",
       "3                          1.0  0.000565  9.551500e+04  95515.000000  \n",
       "4                          0.0  0.000544  5.479452e-04      0.832478  \n",
       "5                          0.0  0.000544  3.581676e-07      0.000544  \n",
       "6                          0.0  0.000544  7.158672e-07      0.001088  \n",
       "7                          0.0  0.000544  1.286400e+04  12864.000000  \n",
       "8                          0.0  0.000502  4.650802e-04      0.706418  \n",
       "9                          0.0  0.000502  3.306146e-07      0.000502  \n",
       "10                         0.0  0.000502  6.607594e-07      0.001004  \n",
       "11                         0.0  0.000502  1.194800e+04  11948.000000  \n",
       "\n",
       "[12 rows x 1753 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res_random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>split</th>\n",
       "      <th>index</th>\n",
       "      <th>B-Lipitor</th>\n",
       "      <th>I-CONCEPT_LESS</th>\n",
       "      <th>I-Severe_pain</th>\n",
       "      <th>B-CONCEPT_LESS</th>\n",
       "      <th>I-Myalgia</th>\n",
       "      <th>B-Pain</th>\n",
       "      <th>B-Myalgia</th>\n",
       "      <th>I-Muscle_weakness</th>\n",
       "      <th>...</th>\n",
       "      <th>B-Feeling_hopeless</th>\n",
       "      <th>B-Feeling_lonely</th>\n",
       "      <th>B-Poor_self-image</th>\n",
       "      <th>I-Poor_self-image</th>\n",
       "      <th>B-Morbid_thoughts</th>\n",
       "      <th>B-Feels_everything_is_futile</th>\n",
       "      <th>B-Transient_global_amnesia</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>macro avg</th>\n",
       "      <th>weighted avg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>train</td>\n",
       "      <td>precision</td>\n",
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       "      <td>0.000005</td>\n",
       "      <td>0.000075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>train</td>\n",
       "      <td>recall</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.008637</td>\n",
       "      <td>0.000572</td>\n",
       "      <td>0.008637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>train</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.017127</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.008637</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.000148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>train</td>\n",
       "      <td>support</td>\n",
       "      <td>825.000000</td>\n",
       "      <td>746.0</td>\n",
       "      <td>425.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>296.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.008637</td>\n",
       "      <td>95515.000000</td>\n",
       "      <td>95515.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>dev</td>\n",
       "      <td>precision</td>\n",
       "      <td>0.009406</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.009406</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>0.000088</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>dev</td>\n",
       "      <td>recall</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>0.009406</td>\n",
       "      <td>0.001890</td>\n",
       "      <td>0.009406</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>dev</td>\n",
       "      <td>f1-score</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.009406</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.000175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>dev</td>\n",
       "      <td>support</td>\n",
       "      <td>121.000000</td>\n",
       "      <td>96.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.009406</td>\n",
       "      <td>12864.000000</td>\n",
       "      <td>12864.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>test</td>\n",
       "      <td>precision</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010629</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.000113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>test</td>\n",
       "      <td>recall</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010629</td>\n",
       "      <td>0.001859</td>\n",
       "      <td>0.010629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>test</td>\n",
       "      <td>f1-score</td>\n",
       "      <td>0.021035</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010629</td>\n",
       "      <td>0.000039</td>\n",
       "      <td>0.000224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>test</td>\n",
       "      <td>support</td>\n",
       "      <td>127.000000</td>\n",
       "      <td>86.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010629</td>\n",
       "      <td>11948.000000</td>\n",
       "      <td>11948.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 1753 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    split      index   B-Lipitor  I-CONCEPT_LESS  I-Severe_pain   \n",
       "0   train  precision    0.008637             0.0            0.0  \\\n",
       "1   train     recall    1.000000             0.0            0.0   \n",
       "2   train   f1-score    0.017127             0.0            0.0   \n",
       "3   train    support  825.000000           746.0          425.0   \n",
       "4     dev  precision    0.009406             0.0            0.0   \n",
       "5     dev     recall    1.000000             0.0            0.0   \n",
       "6     dev   f1-score    0.018637             0.0            0.0   \n",
       "7     dev    support  121.000000            96.0           36.0   \n",
       "8    test  precision    0.010629             0.0            0.0   \n",
       "9    test     recall    1.000000             0.0            0.0   \n",
       "10   test   f1-score    0.021035             0.0            0.0   \n",
       "11   test    support  127.000000            86.0           39.0   \n",
       "\n",
       "    B-CONCEPT_LESS  I-Myalgia  B-Pain  B-Myalgia  I-Muscle_weakness  ...   \n",
       "0              0.0        0.0     0.0        0.0                0.0  ...  \\\n",
       "1              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "2              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "3            351.0      296.0   290.0      210.0              152.0  ...   \n",
       "4              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "5              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "6              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "7             44.0       33.0    46.0       26.0               21.0  ...   \n",
       "8              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "9              0.0        0.0     0.0        0.0                0.0  ...   \n",
       "10             0.0        0.0     0.0        0.0                0.0  ...   \n",
       "11            49.0       29.0    35.0       25.0                6.0  ...   \n",
       "\n",
       "    B-Feeling_hopeless  B-Feeling_lonely  B-Poor_self-image   \n",
       "0                  0.0               0.0                0.0  \\\n",
       "1                  0.0               0.0                0.0   \n",
       "2                  0.0               0.0                0.0   \n",
       "3                  1.0               1.0                1.0   \n",
       "4                  NaN               NaN                NaN   \n",
       "5                  NaN               NaN                NaN   \n",
       "6                  NaN               NaN                NaN   \n",
       "7                  NaN               NaN                NaN   \n",
       "8                  NaN               NaN                NaN   \n",
       "9                  NaN               NaN                NaN   \n",
       "10                 NaN               NaN                NaN   \n",
       "11                 NaN               NaN                NaN   \n",
       "\n",
       "    I-Poor_self-image  B-Morbid_thoughts  B-Feels_everything_is_futile   \n",
       "0                 0.0                0.0                           0.0  \\\n",
       "1                 0.0                0.0                           0.0   \n",
       "2                 0.0                0.0                           0.0   \n",
       "3                 1.0                1.0                           1.0   \n",
       "4                 NaN                NaN                           NaN   \n",
       "5                 NaN                NaN                           NaN   \n",
       "6                 NaN                NaN                           NaN   \n",
       "7                 NaN                NaN                           NaN   \n",
       "8                 NaN                NaN                           NaN   \n",
       "9                 NaN                NaN                           NaN   \n",
       "10                NaN                NaN                           NaN   \n",
       "11                NaN                NaN                           NaN   \n",
       "\n",
       "    B-Transient_global_amnesia  accuracy     macro avg  weighted avg  \n",
       "0                          0.0  0.008637      0.000005      0.000075  \n",
       "1                          0.0  0.008637      0.000572      0.008637  \n",
       "2                          0.0  0.008637      0.000010      0.000148  \n",
       "3                          1.0  0.008637  95515.000000  95515.000000  \n",
       "4                          NaN  0.009406      0.000018      0.000088  \n",
       "5                          NaN  0.009406      0.001890      0.009406  \n",
       "6                          NaN  0.009406      0.000035      0.000175  \n",
       "7                          NaN  0.009406  12864.000000  12864.000000  \n",
       "8                          NaN  0.010629      0.000020      0.000113  \n",
       "9                          NaN  0.010629      0.001859      0.010629  \n",
       "10                         NaN  0.010629      0.000039      0.000224  \n",
       "11                         NaN  0.010629  11948.000000  11948.000000  \n",
       "\n",
       "[12 rows x 1753 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res_mostfreq"
   ]
  }
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