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· JMIR Medical Informatics· 0 citations
Atherosclerotic cardiovascular disease (ASCVD) is the leading global cause of death and evolves over decades through a prolonged subclinical phase, providing a critical opportunity for early detection and prevention. Traditional risk prediction models estimate future cardiovascular risk but may under- or overestimate i...
V. Sorin, Kemi Fatade, Michael F. Morris et al.· Radiographics· 0 citations
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.· PLoS ONE· 0 citations
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