PERSONALIZED PREDICTIVE HEALTH CARE USING ML AND GENERATIVE AI

Abstract

Personalized healthcare has become a crucial aspect of modern medical systems due to the increasing availability of digital health data and advancements in artificial intelligence. This research proposes a Personalized Predictive Healthcare System using Machine Learning (ML) and Generative Artificial Intelligence (GenAI) to analyze patient data and predict potential health risks. The system integrates electronic health records, lifestyle information, and wearable sensor data to generate personalized health predictions and recommendations. Machine learning models such as Random Forest, Support Vector Machine, and Neural Networks are used for disease prediction, while Generative AI assists in generating personalized medical advice and health insights. The proposed framework aims to improve early disease detection, optimize treatment planning, and enhance patient engagement. Experimental results demonstrate that the hybrid approach improves prediction accuracy and provides adaptive healthcare recommendations. The system has the potential to significantly improve preventive healthcare and reduce medical costs.