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

Natural Language Processing (706) Generative Language Models Including ChatGPT (325) AI Language Models in Health Care (61) Machine Learning (55) Chatbots and Conversational Agents (543) Artificial Intelligence (1421) Formative Evaluation of Digital Health Interventions (2491)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57674, first published .
Data Set and Benchmark (MedGPTEval) to Evaluate Responses From Large Language Models in Medicine: Evaluation Development and Validation

Data Set and Benchmark (MedGPTEval) to Evaluate Responses From Large Language Models in Medicine: Evaluation Development and Validation

Data Set and Benchmark (MedGPTEval) to Evaluate Responses From Large Language Models in Medicine: Evaluation Development and Validation

Authors of this article:

Jie Xu1 Author Orcid Image ;   Lu Lu1 Author Orcid Image ;   Xinwei Peng1 Author Orcid Image ;   Jiali Pang1 Author Orcid Image ;   Jinru Ding1 Author Orcid Image ;   Lingrui Yang2 Author Orcid Image ;   Huan Song3, 4 Author Orcid Image ;   Kang Li3, 4 Author Orcid Image ;   Xin Sun2 Author Orcid Image ;   Shaoting Zhang1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

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  2. Andrew A, Tizzard E. Large language models for improving cancer diagnosis and management in primary health care settings. Journal of Medicine, Surgery, and Public Health 2024:100157 View

Books/Policy Documents

  1. Xu H, Xue T, Liu D, Zhang F, Westin C, Kikinis R, O’Donnell L, Cai W. Foundation Models for General Medical AI. View