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

Generative Language Models Including ChatGPT (557) Machine Learning (1821) Artificial Intelligence (1835) Natural Language Processing (829) New Methods (1056) Clinical Informatics (1191) Development and Evaluation of Research Methods, Instruments and Tools (664) Methods and Instruments in Medical Informatics (168) Digital Health Reviews (1583) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (931)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67488, first published .
Accuracy of Large Language Models for Literature Screening in Thoracic Surgery: Diagnostic Study

Accuracy of Large Language Models for Literature Screening in Thoracic Surgery: Diagnostic Study

Accuracy of Large Language Models for Literature Screening in Thoracic Surgery: Diagnostic Study

Authors of this article:

Zhang-Yi Dai1 Author Orcid Image ;   Fu-Qiang Wang1 Author Orcid Image ;   Cheng Shen1 Author Orcid Image ;   Yan-Li Ji1 Author Orcid Image ;   Zhi-Yang Li1 Author Orcid Image ;   Yun Wang1 Author Orcid Image ;   Qiang Pu1 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Colangelo M, Guizzardi S, Meleti M, Calciolari E, Galli C. Performance Comparison of Large Language Models for Efficient Literature Screening. BioMedInformatics 2025;5(2):25 View
  2. Huang S, Wen C, Bai X, Li S, Wang S, Wang X, Yang D. Exploring the Application Capability of ChatGPT as an Instructor in Skills Education for Dental Medical Students: Randomized Controlled Trial. Journal of Medical Internet Research 2025;27:e68538 View