Predict Person Suffer from Heart Attack or not Via Machine Learning

[MithanshuHedau]

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Latest Merged PR Link

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Project Description

The project aims to build a machine learning model to predict whether a person is at risk of having a heart attack based on various health parameters. The dataset typically includes features like age, gender, blood pressure, cholesterol levels, heart rate, and lifestyle factors such as smoking and physical activity.

The process involves:

Data Preprocessing: Handling missing data, scaling features, and encoding categorical variables.
Exploratory Data Analysis (EDA): Identifying patterns and relationships between variables to gain insights.
Model Selection: Training multiple models (e.g., Logistic Regression, Decision Trees, Random Forest, SVM, etc.) and selecting the best performing one.
Evaluation: Using metrics like accuracy, precision, recall, F1-score, and AUC-ROC to evaluate model performance.
Optimization: Tuning hyperparameters and applying cross-validation for better predictions.
The goal is to create a reliable model that can assist in early detection of heart attack risks.

Full Name

Mithanshu Rajesh Hedau

Participant Role

gssoc-ext , hacktoberfest

[github-actions]

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[MithanshuHedau]

@UTSAVS26 , Please assign me this issue with the desired label , so i can further contribute in that .

[github-actions]

✅ This issue has been closed. Thank you for your contribution! If you have any further questions or issues, feel free to join our community on Discord to discuss more!