Table of Contents
"NearestDoctor" is an AI healthcare assistant that uses AI and machine learning algorithms to improve patients' experience by providing them professional medical assistance. Patients will be able to find the nearest doctor to their location, ask about illness symptoms, and schedule an appointment with a doctor based on their availability. Immediate responses will be provided by a chatbot to redeem the needs of our patients using Artificial Intelligence techniques for decision making. Also, our solution offers a very unique concept with developing patient records using Blockchain. The assistant will create a medical record and store it in Blockchain to make them accessible to any of the patient's chosen doctors with granted permission. Thanks to the decentralized nature of Blockchain, patient records would be securely spread among a large number of servers, posing little risk to their sensitive information.
This web application centralizes the schedules and medical services in a single dashboard. This solution offers a real-time overview of the coverage of reports that facilitate the management of resources.
- 🤖 Symptoms Detection: using Artificial Intelligence for specialist recommendation and illness detection.
- 📅 Appointment Scheduling: based on the nearest doctor to your location or the first available appointment.
- 📘 Medical Records: securely stored in the blockchain using smart contracts.
- 💬 Blogs and Forum: using machine learning for patient satisfaction prediction.
- 📈 Real-time reports: using machine learning to offer an overview of many aspects of the application.
- 🙋 Advanced authentication: using facial recognition to match the identity of a doctor, Card ID data extraction, and machine learning for identity verification.
- 🛒 Paramedical e-shop: using machine learning for patient's behavioral analysis prediction.
NearestDoctor is built using MERN Stack technology. You may find below the list of the frameworks/libraries that we used to build our project :
To get a local copy up and running follow these simple example steps.
You may find below the list of things you need to use this project :
- Make sure MongoDB is running on your system.
- You will need to install the "yarn" or "npm" command line.
In order to install the app you need to follow the instructions below :
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Clone the repo
git clone https://github.com/ahlem-phantom/AI-HealthCare-Assistant.git
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Install NPM packages dependencies
npm install
Or
yarn install
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Run the server on
npm run development
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Open localhost:3000 in the browser and that's it you can enjoy the project 🎉!
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.
See the open issues for a list of proposed features (and known issues).
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Phase 1 : Project Study, Requirement Analysis and Prototyping
- Problematic definition
- State of the art
- Preliminary Feasibility Study
- Solution & functional/technical requirements
- Wireframes of the solution
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Phase 2 : Advanced Features Specification, Application Design & Realization
- Data Model
- Physical architecture and technical environments
- Specification of the advanced features
- Advanced Feasibility Study (Cases studied problems and Results - development Back-end)
- Development of static user interfaces (Front-end)-> depending on the project
- First NodeJS components (scenarios and case studies tests)
- Static User Interfaces (Front-end)
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Phase 3.1 : Realization Of Advanced Features, Deployment And Tests
- Implementation of the solution (V1)
- Continuation Back-End development
- Collecting and using flow from external application(Phase 2 + Phase 3)
- Consuming REST services by the front-end
- Development of final user interfaces (Front-end)
- Exposing REST services by the back-end Node.js
- Integration
- Implemented Application V1
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Phase 3.2 : Realization Of Advanced Features, Deployment And Tests
- Finalization of final delivrable (V2)
- Final Integration/Deployment of the solution
- Tests
- Implemented Application V2
- Tests results
If you have a suggestion that would make this project better, please fork the repo and create a pull request. Any contributions you make are greatly appreciated. Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b Yourbranch) - Commit your Changes (
git commit -m 'Add some features to project') - Push to the Branch (
git push origin Yourbranch) - Open a Pull Request
Project Mentor : [email protected]
Project Members :
 Ahlem Laajili |
 Skander Turki |
 Syrine Zahras |
 Hichem Ben Zammal |
 Nesrine Ben Mahmoud |
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Developed with 💕 by AlphaCoders.