An Ai-Powered Predictive Health Nexus for Proactive Disease Identification and Personalized Patient Outcome Forecasting

Heart disease is a leading cause of mortality worldwide, making early detection essential. This project presents a Smart Heart Disease Prediction System, an AI-powered web application that predicts the likelihood of heart disease using machine learning based on clinical parameters such as age, sex, chest pain type, blood pressure, cholesterol, fasting blood sugar, ECG results, maximum heart rate, exercise-induced angina, old peak, and ST slope. The system uses a trained classification model deployed through a Fast API backend for real-time prediction, with a user-friendly frontend built using HTML, CSS, and JavaScript. It classifies patients into high or low risk, provides probability scores, personalized health insights, and recommended actions for preventive care. An interactive dashboard visualizes key data patterns like age, gender, and disease distribution, enhancing understanding. By integrating machine learning, web technologies, and data visualization, the system offers a scalable and efficient solution for early screening, telemedicine support, and improved healthcare decision making.