❤️ Heart Disease Prediction App

This project is a machine learning web app that predicts the likelihood of heart disease based on patient data. It uses a Logistic Regression model trained on the UCI Heart Disease dataset.

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🚀 Features

• Predicts heart disease risk using 13 clinical parameters.
• Interactive web interface built with Streamlit.
• Displays model accuracy and performance metrics.
• Shows sample data for reference.

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📊 Model Performance

• Training Accuracy: 85%
• Test Accuracy: 82%
• Precision / Recall / F1-Score: ~82% balanced across classes

(Note: This model is for educational purposes and not for real medical use.)

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🛠️ Installation

1. Clone the repository:

   git clone https://github.com/your-username/heart-disease-prediction.git

2. Install dependencies: pip install streamlit scikit-learn pandas pillow

3.🖥️ Running the App In your terminal, run:

streamlit run app.py

Your browser will open at http://localhost:8501.

⚠️ Disclaimer This project is not a medical diagnostic tool. Predictions are for demonstration and educational purposes only.

Dataset: UCI Heart Disease Data

AUTHOR: Shruthikha S.