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Evaluating base and retrieval augmented LLMs with document or online support for evidence based neurology
26
Zitationen
3
Autoren
2025
Jahr
Abstract
Effectively managing evidence-based information is increasingly challenging. This study tested large language models (LLMs), including document- and online-enabled retrieval-augmented generation (RAG) systems, using 13 recent neurology guidelines across 130 questions. Results showed substantial variability. RAG improved accuracy compared to base models but still produced potentially harmful answers. RAG-based systems performed worse on case-based than knowledge-based questions. Further refinement and improved regulation is needed for safe clinical integration of RAG-enhanced LLMs.
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