Retrieval augmented generation for 10 large language models and its generalizability in assessing medical fitness

Large Language Models (LLMs) hold promise for medical applications but often lack domain-specific expertise. Retrieval Augmented Generation (RAG) enables customization by integrating specialized knowledge. This study assessed the accuracy, consistency, and safety of LLM-RAG models in determining surgical fitness and delivering preoperative instructions using 35 local and 23 international guidelines. Ten LLMs (e.g., GPT3.5, GPT4, GPT4o, Gemini, Llama2, and Llama3, Claude) were tested across 14 cl

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ethics.ai (5 April 2025), “Retrieval augmented generation for 10 large language models and its generalizability in assessing medical fitness,” evidence record 9735, https://ethics.ai/record/9735 (originally published by OpenAlex).

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