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arXiv AI By Abinitha Gourabathina, Haoran Zhang, Yuexing Hao, Walter Gerych, Marzyeh Ghassemi

Sense and Sensitivity: Benchmarking LLM Clinical Triage Recommendations with Physician Experts

Read the original on arXiv AI →

The paper introduces a benchmark of over 6,000 clinical triage scenarios, 7,000 physician annotations, and 225,000 large language model (LLM) responses to assess how LLMs perform under realistic variations in clinical text. The study finds that LLMs tend to recommend unnecessary care more often than physicians, especially when the input text is perturbed, and that LLM recommendations are more sensitive to gender and tone changes than human recommendations. These findings underscore the importance of deployment‑oriented evaluations that reflect expert physician behavior.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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