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

Digital Health Reviews (1772) Artificial Intelligence (2227) Machine Learning (2151) Reviews (141) Pregnancy Information, Education and Lifestyle Interventions (413) Diabetes Reviews and Scoping Studies (39)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/79729, first published .
Predictive Performance of Artificial Intelligence Algorithms for Gestational Diabetes Mellitus in Pregnant Women: Systematic Review and Meta-Analysis

Predictive Performance of Artificial Intelligence Algorithms for Gestational Diabetes Mellitus in Pregnant Women: Systematic Review and Meta-Analysis

Predictive Performance of Artificial Intelligence Algorithms for Gestational Diabetes Mellitus in Pregnant Women: Systematic Review and Meta-Analysis

Authors of this article:

Yingni Liang1 Author Orcid Image ;   Anran Dai1 Author Orcid Image ;   Meiyan Luo2 Author Orcid Image ;   Zhuolian Zheng1 Author Orcid Image ;   Jiayu Shen1 Author Orcid Image ;   Yinhua Su1 Author Orcid Image ;   Zhongyu Li1 Author Orcid Image
Article Authors Cited by Tweetations (1) Metrics

Yingni Liang   1 * , MM ;   Anran Dai   1 * , MM ;   Meiyan Luo   2 * , MM ;   Zhuolian Zheng   1 , MM ;   Jiayu Shen   1 , MM ;   Yinhua Su   1 * , PhD ;   Zhongyu Li   1 * , PhD

1 School of Nursing, University of South China, Hunan, China

2 Department of Obstetrics, Second Affiliated Hospital of the University of South China, Hunan, China

*these authors contributed equally

Corresponding Author:

  • Zhongyu Li, PhD
  • School of Nursing, University of South China
  • No. 28, Changsheng West Road, Hengyang
  • Hunan 421001
  • China
  • Phone: 867348281809
  • Email: lzhy1023@usc.edu.cn