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

Artificial Intelligence (2134) Misinformation and Disinformation Outbreaks and Information Prevalence Studies (93) Bots and AI Approaches to Detect and Counter Misinformation (20) Generative Language Models Including ChatGPT (708) JMIR Theme Issue: COVID-19 Special Issue (2555)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/66098, first published .
Use of Retrieval-Augmented Large Language Model for COVID-19 Fact-Checking: Development and Usability Study

Use of Retrieval-Augmented Large Language Model for COVID-19 Fact-Checking: Development and Usability Study

Use of Retrieval-Augmented Large Language Model for COVID-19 Fact-Checking: Development and Usability Study

Authors of this article:

Hai Li1 Author Orcid Image ;   Jingyi Huang1 Author Orcid Image ;   Mengmeng Ji2 Author Orcid Image ;   Yuyi Yang3 Author Orcid Image ;   Ruopeng An4 Author Orcid Image
Article Authors Cited by (6) Tweetations Metrics

Hai Li   1 * , PhD ;   Jingyi Huang   1 * , MA ;   Mengmeng Ji   2 , MBBS, PhD ;   Yuyi Yang   3 , MB, MPH ;   Ruopeng An   4 , MPP, PhD

1 School of Economics and Management, Shanghai University of Sport, Shanghai, China

2 Department of Surgery, Division of Public Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, United States

3 Division of Computational and Data Sciences, Washington University in St. Louis, St. Louis, MO, United States

4 Constance and Martin Silver Center on Data Science and Social Equity, Silver School of Social Work, New York University, New York, NY, United States

*these authors contributed equally

Corresponding Author:

  • Hai Li, PhD
  • School of Economics and Management
  • Shanghai University of Sport
  • 650 Hengren Road
  • Yangpu District
  • Shanghai 200000
  • China
  • Phone: 86 13816490872
  • Email: lihai1107@hotmail.com