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E. Klang

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Open access Aug 2026

AI Scribe Safety: Measuring What Happens After Signing

Abstract Coiera and Fraile-Navarro question whether AI scribes are being evaluated on metrics that truly impact care. While current evaluations focus on the quality of the initial draft, signed clinical notes are dynamic, as their content can be copied, summarized, coded, and re-ingested by downstream AI tools. We argu...

V. Sorin, E. Klang · 0 citations
Aug 2026

Sociodemographic bias in LLMs' clinical decision-making for dizziness.

LLM clinical recommendations varied by sociodemographic descriptors, particularly under diagnostic uncertainty, suggesting structured inputs may mitigate bias in clinical AI systems.

Idit Tessler, Mahmud Omar, A. Wolfovitz et al. · 0 citations
Open access Jul 2026

Case-matched retrieval improves textual alignment of LLM-generated radiology impressions

Dynamic, case-matched retrieval improved alignment of LLM-generated CT pulmonary angiography impressions with reference impressions on automated text-similarity metrics in a retrospective IRB-approved study.

V. Sorin, Jeremy D. Collins, Lewis Hahn et al. · 0 citations

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