hackathon-brain-stroke

A machine learning-powered web application to predict the risk of brain stroke based on user health inputs.

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📌 Features

✅ User Authentication (Signup/Login)
✅ Stroke Risk Prediction using RandomForestClassifier
✅ Interactive Form for Input Data
✅ Dynamic Result Display
✅ Profile Management

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🚀 Tech Stack

• Frontend: HTML, CSS, JavaScript
• Backend: Flask
• Machine Learning Model: RandomForestClassifier (saved as stroke_model.joblib)
• Database: SQLite3
• Dataset: brain_stroke.csv

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📂 Project Structure

/hackathon-brain-stroke
│── static/                # Static files (CSS, JS)
│── templates/             # HTML templates
│── app.py                 # Main Flask application
│── save_model.py          # Model training script
│── stroke_model.joblib    # Pre-trained ML model
│── brain_stroke.csv       # Dataset used for training
│── requirements.txt       # Dependencies
│── edit_profile.html      # Edit user profile page
│── login.html             # Login page
│── profile.html           # User profile
│── result.html            # Prediction result page
│── signup.html            # Signup page
│── stroke.html            # Stroke prediction form

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🔮 Future Enhancements

🔹 Improve model accuracy with deep learning
🔹 Deploy the project online (e.g., Render, Vercel, or AWS)
🔹 Add real-time health monitoring features

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