Papers by Rahul G Krishnan
Agentic Medical Knowledge Graphs Enhance Medical Question Answering: Bridging the Gap Between LLMs and Evolving Medical Knowledge (2025.findings-emnlp)
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| Challenge: | Large Language Models have greatly advanced medical Question Answering (QA) however, the rapid evolution of medical knowledge and manual updating of domain-specific resources can undermine reliability of these systems. |
| Approach: | AMG-RAG automates the construction and continuous updating of Medical Knowledge Graph (MKG) . afriq: rapid evolution of medical knowledge and manual updating can undermine reliability of LLMs . |
| Outcome: | AMG-RAG achieves an F1 score of 74.1% on MEDQA and an accuracy of 66.34% on medMCQA. |