Smart Health Prediction Using Data Mining

This project focuses on developing a smart health prediction system using data mining techniques to enhance early detection and prevention of heart disease. By integrating electronic health records, medical databases, and wearable device data, the system leverages classification, clustering, and predictive modeling to identify key risk factors and estimate disease likelihood. The proposed approach enables healthcare providers to make informed decisions, personalize treatment plans, and implement proactive interventions, ultimately improving patient outcomes and reducing healthcare costs. This research contributes to the advancement of data-driven healthcare solutions, fostering precision medicine and predictive analytics in the medical field.