Real-Time Data Integration and Analysis for Heart Disease Prediction Using Machine Learning

The " Heart Disease Risk Assessment Web App" is a cutting-edge web application that uses sophisticated machine learning techniques to deliver individualized cardiovascular risk information. The app uses information from the Behavioral Risk Factor Surveillance System (BRFSS) 2022 to determine personalized risk scores and provide useful advice based on user inputs including age, BMI, physical activity, smoking status, and medical history. While SHAP (SHapley Additive exPlanations) improves transparency by clarifying feature relevance, the app uses advanced models, such as Easy Ensemble with LightGBM, to handle class imbalance and guarantee reliable predictions. With the help of Streamlit, the software effectively reduces the risk of heart disease and encourages proactive health management by fusing accuracy, accessibility, and user interaction to provide people with useful information. Keywords—health evaluation,heart disease, cardiovascular health,SHAP,Simple Ensemble Classifier Model LightGBM,Streamlit,BRFSS dataset,Individualized health advice,Handling class imbalance