Evidence-grounded medical RAG system that retrieves FDA and NICE drug guidelines, generates cited answers, and safely refuses unsupported queries to minimize hallucinations.
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Updated
Feb 15, 2026 - Python
Evidence-grounded medical RAG system that retrieves FDA and NICE drug guidelines, generates cited answers, and safely refuses unsupported queries to minimize hallucinations.
MedRAG is a multi-modal medical retrieval and generation system that combines research literature and radiological images to deliver evidence-grounded, context-aware medical insights. The system integrates semantic search, citation-aware ranking, and controlled language generation to support exploratory medical research and decision support.
A production-style Medical RAG chatbot built with FastAPI, LangChain, Pinecone, and Google Gemini. Uses document ingestion and vector search to provide grounded, context-aware medical responses with strict safety constraints.
Medical RAG Chatbot is a Retrieval-Augmented Generation chatbot that answers medical questions using PDF knowledge sources, Groq LLM, Hugging Face embeddings, FAISS vector search, and LangChain orchestration. Includes Flask APIs, HTML/CSS UI, Dockerized deployment, Jenkins CI/CD, and Trivy image scanning on AWS.
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