Agentic Medical Graph-RAG (AMG-RAG) features autonomous Knowledge Graph (KG) evolution through Large Language Model (LLM) agents that extract entities and relations from live sources with provenance tracking; graph-conditioned retrieval that maps queries onto the Medical Knowledge Graph (MKG) to guide evidence selection; and reasoning over structured context where the answer generator utilizes both textual passages and traversed sub-graphs for transparent, multi-hop reasoning.

Authors

• Person: Not available Organization: arXiv
  Bridging the Gap Between LLMs and Evolving Medical Knowledge

Sources

• Bridging the Gap Between LLMs and Evolving Medical Knowledge arxiv.org arXiv via serper

Referenced by nodes (3)

• Knowledge Graph concept
• Medical Knowledge Graph concept
• AMG-RAG concept