AI based Supervised Learning Approach for Heart Disease Prediction and Prevention

Heart disease remains a leading cause of mortality worldwide, making early detection and prevention critical. This project, "AI based Supervised Learning Approach for Heart Disease Prediction and Prevention," employs Bagging Classifier and Deep Learning techniques to predict heart disease risk, classify its stages, and recommend preventive measures. The Bagging Classifier enhances accuracy by reducing variance through ensemble learning, while deep learning models analyze patient data—including age, sex, blood pressure, and heart rate—to determine disease severity. The system is trained on realtime and historical medical records to improve reliability. Additionally, it provides personalized preventive recommendations based on a patient's risk level and disease stage, guiding users on lifestyle modifications, dietary changes, and medical interventions. The proposed system offers a fast, accurate, and cost-effective solution to reduce heart disease-related mortality and improve patient outcomes.