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Clinician Perspectives on AI-Generated Drafts of Patient Test Result Explanations

Shreya Shah, Abishek Nair, Kirsten Murtagh, P. Stephen, Kyle Vogt, Danyelle Clutter, Liban Sheikh, H. Schmidt, Margaret Smith, Arun Lakhotia, Lance Bullock, Aditya Bhasin, Michael A. Pfeffer, Christopher Sharp, Steven Lin, Patricia García

2025JAMA Network Open8 citationsDOIOpen Access PDF

Abstract

This quality improvement study evaluates clinician perspectives on the usability and utility of generative artificial intelligence (AI)–based large language model tool to draft result comments for laboratory, imaging, and pathology results.

Topics & Concepts

UsabilityGenerative grammarTest (biology)Computer scienceQuality (philosophy)Artificial intelligenceNatural language processingPsychologyData scienceHuman–computer interactionEpistemologyBiologyPhilosophyPaleontologyArtificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical ImagingAI in cancer detection
Clinician Perspectives on AI-Generated Drafts of Patient Test Result Explanations | Litcius