Secure Health Management and Prediction System for Chronic Diseases

The Secure Health Management and Prediction System for Chronic illnesses has transformed healthcare by predicting and controlling chronic illnesses using user-provided data. It lowers healthcare expenses by combining machine learning, data analytics, and cloud computing. With strong safeguards such as encryption and authentication, the system protects data privacy and security. Its HIPAA compliance and focus on patient privacy make it helpful in rural Sri Lanka, where experts are few. Using machine learning, data analytics, and cloud computing, the research study proposes a secure health management and prediction system for chronic diseases. Based on medical information, the algorithm forecasts chronic illnesses such as diabetes and cardiovascular disorders. For diabetes and cardiovascular disease prediction, it employs techniques such as Decision Tree, Linear Regression, Random Forest, Support V ector Machine, Logistic Regression, and Naive Bayes. Based on patient feedback, the system also assesses insurance costs and suggests providers.