AI Diagnostic Assistant

AI Diagnostic Assistant is a knowledge-graph powered medical support system designed for rapid and explainable differential diagnosis. It combines Retrieval-Augmented Generation (RAG), RDF ontologies, and SPARQL querying to deliver structured and context-aware medical insights. The backend is built with FastAPI and supports both semantic search and knowledge graph reasoning workflows. A modern Next.js frontend provides an interactive interface for submitting diagnostic questions and viewing generated explanations, query traces, and results. The project also integrates Chroma vector embeddings for efficient ontology retrieval and contextual reasoning. It supports scalable deployment using platforms like Render and Vercel. The system was designed to explore how AI, knowledge representation, and semantic web technologies can improve clinical decision support. Technologies used include Python, FastAPI, Next.js, RDF, SPARQL, ChromaDB, and OpenAI APIs.