The rapid advancement of technology in healthcare has created opportunities for improving patient care through intelligent systems. Traditional healthcare systems often rely on manual processes, fragmented data storage, and delayed diagnosis, which can lead to inefficiencies and errors. There is a growing need for an integrated, intelligent, and automated healthcare system that can provide real-time insights and predictive analysis.

This project presents a Smart Healthcare System; a web-based application developed using Python (Flask framework), Machine Learning algorithms, and Gemini Flash 2.5 AI chatbot. The system enables patients to register, store medical history, input symptoms, and receive disease predictions based on trained machine learning models. It also includes risk prediction for diseases such as diabetes and heart disease.

The system integrates a chatbot that provides real-time health-related guidance and suggestions while ensuring safety through disclaimers. Additional features include appointment booking, dashboard visualization, emergency alerts, and medicine reminders.

The proposed system aims to improve healthcare accessibility, reduce manual effort, and support early disease detection using intelligent technologies.