This Flask web application integrates three machine learning prediction models to provide health predictions for heart disease, diabetes, and breast cancer. The app uses the following models:
- Heart Disease Prediction
- Diabetes Prediction using Random Forest Classifier
- Breast Cancer Detection
To get started, follow these steps:
-
Clone the repository:
git clone https://github.com/yourusername/your-repo-name.git cd your-repo-name -
Create a virtual environment:
python -m venv venv source venv/bin/activate # On Windows use `venv\Scripts\activate`
-
Install the dependencies:
pip install -r requirements.txt
-
Run the application:
flask run
The app will be accessible at http://127.0.0.1:5000.
- Heart Disease Prediction: Navigate to the Heart Disease Prediction page, fill out the form with the required medical information, and click "Predict" to get the prediction.
- Diabetes Prediction: Navigate to the Diabetes Prediction page, fill out the form with the necessary details, and click "Predict" to get the prediction.
- Breast Cancer Detection: Navigate to the Breast Cancer Detection page, provide the relevant data, and click "Predict" to get the prediction.
The heart disease prediction model uses various medical parameters such as age, sex, blood pressure, cholesterol levels, and more to predict the likelihood of a heart disease.
The diabetes prediction model uses a Random Forest Classifier to predict the likelihood of diabetes based on factors like glucose levels, blood pressure, skin thickness, insulin levels, BMI, age, etc.
The breast cancer detection model classifies whether a tumor is benign or malignant based on several features computed from a digitized image of a fine needle aspirate (FNA) of a breast mass.
Contributions are welcome! Please fork this repository and submit a pull request for any changes you'd like to make.
This project is licensed under the MIT License - see the LICENSE file for details.