Medical reports contain multiple parameters (age, BP, cholesterol, etc.), making it difficult to quickly assess heart disease risk. This system allows users to enter their report values and get an instant prediction.
- User Login & Signup
- Real-time Prediction
- Prediction History stored in PostgreSQL
- Admin Dashboard
- Dataset: Kaggle (~916 rows)
- Algorithm: Naive Bayes
- Accuracy: 93.2%
- F1 Score: 0.9208
- Frontend: JSP
- Backend: Java Servlets
- Database: PostgreSQL
- ML: Python (Flask API + Scikit-learn)
JSP → Servlet → Flask API → ML Model → Result → Database
This project focuses on integrating Machine Learning into a real-world full-stack system.