Ai-Driven Web-Based Heart Disease Prediction System With User-Centric Features

Abstract

Heart disease continues to represent a major global health burden, underscoring the importance of accessible tools that can help individuals understand their potential risk. This work introduces a web-based heart disease assessment platform that combines machine learning with a user-oriented interface. A Random Forest model processes user-submitted medical information to generate immediate risk predictions, while the web system supports secure login, personalized dashboards, and historical record tracking. Built with React.js, Express.js/Node.js, and MySQL, the platform emphasizes practicality, responsiveness, and data protection. The system is deployed through Railway for consistent cloud availability. Future enhancements include support for additional languages and integration with real-time health-monitoring devices.