Proposes a clinician-centered framework to enhance diagnosis using large language models while ensuring patient safety.
Diagnostic error remains a major patient safety challenge in hospital medicine. Large language models (LLMs) are increasingly used by clinicians to aid in diagnosis, yet most lack a structured approach for doing so safely and effectively. In this piece, we propose a practical, clinician-centered framework for LLM-assisted diagnosis. The 5R's Framework promotes a human-in-the-loop approach that harnesses LLMs to reduce diagnostic error while preserving critical reasoning skills.
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Barish et al. (2026) studied this question.
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