CardioSense.AI is an advanced AI-powered heart disease prediction system designed to provide early risk assessment based on key health indicators. Leveraging XGBoost and an AI chatbot, it delivers instant Yes/No predictions, personalized risk scores, and actionable health recommendations to empower individuals in their healthcare journey.
🔬 Theme: Healthcare
📜 Problem Statement: Early disease prediction for heart health
💡 Solution: AI-based risk prediction with user-friendly reports and chatbot assistance
| Feature | Benefit |
|---|---|
| ✅ Early Detection | Helps in preventing severe heart complications |
| ✅ Affordable & Accessible | Eliminates the need for costly medical tests |
| ✅ AI Chatbot Support | 24/7 assistance for health-related queries 🤖 |
| ✅ Downloadable Health Reports | Easy sharing with medical professionals 📄 |
| ✅ Scalability | Seamless integration with hospitals & telemedicine services 🏥 |
- 🏥 AI-driven heart disease risk prediction using XGBoost with high accuracy
- ✅ Instant Diagnosis: Yes/No result with an explanatory risk percentage
- 📊 Personalized Health Insights: Tailored recommendations based on user data
- 🤖 AI Chatbot Support: 24/7 user assistance for health queries
- 📄 Downloadable PDF Reports: Easily share results with healthcare professionals
- 📡 Cloud-Based & Scalable: Ready for integration into telemedicine platforms
| Step | Description |
|---|---|
| 1️⃣ User Input | Users enter health parameters (age, BMI, smoking status, glucose levels, etc.) |
| 2️⃣ Data Preprocessing & Feature Selection | Data is cleaned, and key features are selected |
| 3️⃣ XGBoost Model Processing | AI model predicts heart disease risk |
| 4️⃣ Prediction Output | Displays Yes/No risk level & risk percentage |
| 5️⃣ AI Chatbot & Report Generation | Provides real-time guidance & downloadable reports 📄 |
🎥 Demo Video: Watch Now
📂 Dataset: Kaggle Dataset
📑 Project Report & Video: Google Drive
| Impact Category | Expected Improvement |
|---|---|
| 📉 Reduction in Heart Disease Mortality | 25% |
| 📈 Increase in Preventive Checkups | 50% |
| 💰 Healthcare Cost Savings | 30-40% |
| Technology | Purpose |
|---|---|
| 🐍 Python | AI model development |
| ⚡ XGBoost | Machine Learning algorithm |
| 🌐 Flask | Web Application backend |
| 📊 Streamlit | Interactive visualization |
| 🤖 AI Chatbot | Real-time user assistance |
| ☁️ Cloud Deployment | Scalability and accessibility |
🔹 Integration with Wearable Devices (Apple Watch, Fitbit)
🔹 Mobile App Development for real-time tracking 📱
🔹 Expansion to other disease predictions using AI
🔹 Multi-language Support for global accessibility 🌍
| Name | Role |
|---|---|
| 👨🎓 Srinjoy Pramanik | Backend Development(team lead) |
| 👨🎓 Soumyajit Dutta | Backend & Data Processing |
| 👨🎓 Arpan Chowdhury | Frontend & UI/UX |
| 👨🎓 Syed Md. Musharraf | Chatbot & Integration ML |
| 👨🎓 Rudrasish Dutta | ML Expert |
# Clone the repository
$ git clone https://github.com/yourusername/CardioSense.AI.git
# Navigate to the project folder
$ cd CardioSense.AI
# Install dependencies
$ pip install -r requirements.txt
# Run the application
$ python app.pyWe welcome contributions! 🎉
- Fork the repository 🍴
- Create a branch for your feature/fix 🌱
- Commit your changes with a clear message ✅
- Submit a pull request 🔁
Let's work together to revolutionize heart disease prediction! ❤️
📩 Have feedback? Open an issue or drop us a message!
🏅 Developed for Healthcare Innovation Challenges
🏆 Hackathon Participation & Awards
🎖️ Recognized for AI-driven Predictive Healthcare Solutions
🔖 MIT License - Feel free to use, modify, and enhance CardioSense.AI 🚀
📧 Email us at: [email protected]
🌟 If you like this project, give it a star ⭐ on GitHub!
🚀 Let's make heart disease prediction accessible for everyone! 💖