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arXiv AI By Prabhjot Singh, Pritam Deka, Vijay Chennareddy

Same Illness, Different Voice: Restating the Patient's Account Narrows Narrative Anchoring in Clinical Language Models

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The study evaluates how clinical language models perform when patient narratives are presented in different voices—clinical, socioeconomic, and cultural—using 1,000 MedQA cases paired with three retellings each. All 12 tested models show a significant drop in accuracy (about 26% more errors) when the patient speaks in a marked voice, a penalty that persists even when the original vignette is included verbatim and is not explained by measured retelling properties. The authors find that rewriting the patient’s account into a clinical vignette before answering can halve this accuracy gap, though structured schema pipelines and additional reasoning tools offer limited improvements.

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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