Heart Disease Predictor

This project aims to develop Health Management system by using a machine learning model for predicting the likelihood of heart disease in patients. This can predict 5 different types of disease :- 'Arrhythmia','Coronary Artery Disease','Heart Disease','Hypertension', 'Stroke'.

Model

We have implemented a classification model using a combination of feature engineering and bases on S.V.C machine learning algorithm. The model is trained on the dataset to learn patterns and make predictions on new, unseen data.

Setup 🔧

1. Clone the repository:

   git clone https://github.com/anki-space/heart_disease_predicton

2. Create and activate a virtual environment:

   python -m venv venv
   venv\Scripts\activate

3. Install the required packages:

   cd heart_diesease_predict
   pip install -r requirements.txt

4. Apply database migrations:

   python manage.py migrate

5. Run the development server:

   python manage.py runserver

   Access the application at http://127.0.0.1:8000.

Results

The performance of the heart disease predictor model is evaluated using various metrics such as accuracy, precision, recall, and F1 score.

Classification Report on Test Data:

          precision    recall  f1-score   support

       0       1.00      0.88      0.94        50
       1       1.00      0.96      0.98        50
       2       0.84      0.96      0.90        54
       3       0.90      1.00      0.95        52
       4       1.00      0.83      0.91        36

accuracy                           0.93       242

The results indicate the effectiveness of the model in predicting heart disease.