❤️ Heart & Stroke Disease Risk Predictor

Built with Streamlit

🔗 Live Web App:
👉 https://heartstroke.streamlit.app/

This project predicts the risk of heart disease using a trained Machine Learning model.
Users can input their health parameters and instantly receive a risk score with visualizations.

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🚀 Features

• 🖥️ Beautiful & Organized UI \
• 🤖 KNN-based ML model\
• 📊 Risk Gauge Meter\
• 🔢 Handles all numeric & categorical inputs\
• 📈 Works with real clinical parameters\
• ⚡ Fast predictions\
• 📝 Inline explanations & guidance\
• 🛡️ Medical disclaimer included

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📷 Screenshots

📌 Landing Page

📌 Prediction Result & Gauge

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🧠 ML Model Details

• Algorithm → K-Nearest Neighbors (KNN)
• Preprocessing → StandardScaler
• Model Files:
  • knn_heart_model.pkl
  • heart_scaler.pkl
  • heart_columns.pkl
• Dataset → UCI Heart Disease Dataset

The model predicts: - 1 → High Risk - 0 → Low Risk

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🛠️ Tech Stack

Component	Technology
Frontend	Streamlit
Backend	Python
ML Model	Scikit-Learn
Visualization	Plotly
Deployment	Streamlit Cloud
Version Control	Git & GitHub

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📦 Installation

1️⃣ Clone the repository

git clone https://github.com/Vikaumar/HeartStrokePredictor.git
cd HeartStrokePredictor

2️⃣ Install dependencies

pip install -r requirements.txt

3️⃣ Run the Streamlit App

streamlit run app.py

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📁 Project Structure

📦 HeartStrokePredictor
 ┣ 📜 app.py
 ┣ 📜 knn_heart_model.pkl
 ┣ 📜 heart_scaler.pkl
 ┣ 📜 heart_columns.pkl
 ┣ 📜 requirements.txt
 ┣ 📂 screenshots
 ┃ ┣ 📜 Screenshot1.png
 ┃ ┣ 📜 Screenshot2.png
 ┃ ┗ 📜 Screenshot3.png
 ┗ 📜 README.md

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🌐 Deployment

This app is deployed using Streamlit Cloud:
🌍 https://heartstroke.streamlit.app/

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⚕️ Medical Disclaimer

This tool is for educational purposes only.
It does not provide medical diagnosis.
Always consult certified healthcare professionals for medical decisions.

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👨‍💻 Developer

Vikas Kumar

If you like this project, please ⭐ the repository!

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🎉 Thank you for exploring this project!