Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study

BackgroundAlthough patients have easy access to their electronic health records and laboratory test result data through patient portals, laboratory test results are often confusing and hard to understand. Many patients turn to web-based forums or question-and-answer (Q&A) sit...

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Bibliografische Detailangaben

Hauptverfasser:	Zhe He, Balu Bhasuran, Qiao Jin, Shubo Tian, Karim Hanna, Cindy Shavor, Lisbeth Garcia Arguello, Patrick Murray, Zhiyong Lu
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	JMIR Publications 2024-04-01
Schriftenreihe:	Journal of Medical Internet Research
Online-Zugang:	https://www.jmir.org/2024/1/e56655
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