This paper is in the following e-collection/theme issue:

Generative Language Models Including ChatGPT (433) AI Language Models in Health Care (90) Electronic Health Records (1131) Artificial Intelligence (1626) Clinical Information and Decision Making (1570)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67967, first published .
Large Language Model–Based Assessment of Clinical Reasoning Documentation in the Electronic Health Record Across Two Institutions: Development and Validation Study

Large Language Model–Based Assessment of Clinical Reasoning Documentation in the Electronic Health Record Across Two Institutions: Development and Validation Study

Large Language Model–Based Assessment of Clinical Reasoning Documentation in the Electronic Health Record Across Two Institutions: Development and Validation Study

Authors of this article:

Verity Schaye1, 2 Author Orcid Image ;   David DiTullio1 Author Orcid Image ;   Benedict Vincent Guzman3 Author Orcid Image ;   Scott Vennemeyer4 Author Orcid Image ;   Hanniel Shih4 Author Orcid Image ;   Ilan Reinstein2 Author Orcid Image ;   Danielle E Weber5, 6 Author Orcid Image ;   Abbie Goodman5, 6 Author Orcid Image ;   Danny T Y Wu4 Author Orcid Image ;   Daniel J Sartori1 Author Orcid Image ;   Sally A Santen7 Author Orcid Image ;   Larry Gruppen8 Author Orcid Image ;   Yindalon Aphinyanaphongs3 Author Orcid Image ;   Jesse Burk-Rafel1, 2 Author Orcid Image
Article Authors Cited by Tweetations (1) Metrics
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Scott Vennemeyer Scott Vennemeyer @ScottVennemeyer

Clinical reasoning is an essential skill; yet, physicians often receive limited feedback. Our teams at NYU and UC looked to solve this problem with Large Language Models and AI! Excited about this incredible team, led by @vschaye and with many others! https://t.co/8bH2gtQxiB

8:25 PM · Mar 23, 2025

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