Development of a Medical Chatbot System with Semantic Search and Real-Time Response

This research presents a comprehensive medical chatbot system designed to understand user queries semantically and provide accurate real-time responses. The system integrates FastAPI backend, Sentence-Transformers MiniLM model, and a React-based frontend for interactive communication. Extensive testing demonstrates its capability to handle multiple medical queries efficiently while suggesting appropriate medications or home remedies. The methodology includes semantic similarity computation, database management, and interactive frontend design. Results indicate significant improvements in query response accuracy, user engagement, and response time. The research provides a foundation for deploying intelligent healthcare support systems in practical applications. Keywords: Medical chatbot, Semantic search, FastAPI, React, Machine learning, Real-time response, Healthcare A