Clinical RAG — Medical Q&A System
Built a Clinical RAG medical Q&A system by indexing medical notes into a vector database and performing semantic retrieval for question answering. Used embedding models with FAISS to enable similarity search over medical text, then integrated the retrieved context to answer user queries. The work focused on preparing and leveraging medical data for retrieval and QA performance. • Created semantic search over medical notes using vector embeddings • Used FAISS for similarity indexing and retrieval • Designed a medical Q&A flow grounded in retrieved content • Prepared medical text data for retrieval-based QA