RAG for medical data: improving healthcare AI accuracy

This post details the application of RAG for medical data, focusing on improving accuracy by connecting LLMs to trusted medical datasets, reducing hallucinations, and supporting clinical decision-making through specific use cases like clinical decision support, medical research search, and patient question-answering. It outlines the process of building medical RAG systems by preparing and indexing medical datasets, and evaluating outputs, and introduces agentic RAG in healthcare for complex tasks.