Accessibility settings

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

Digital Health Reviews (3651) Reviews (295) Reviews on Diabetes Technologies and Innovations (92) Machine Learning (3154) Pregnancy Information, Education and Lifestyle Interventions (472) Artificial Intelligence (4743)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/79729, first published .
Pregnant woman reading a book on a couch, touching her belly.

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 (4) Tweetations (2) Metrics

Journals

  1. Chatterjee S, Pramanik S, Kapoor N, Kalra S. Technology in Diabetes: A Year in Review. Diabetes Therapy 2026;17(6):823 View
  2. Bashir S, Salad H, Abdullahi Y, Abdi Y, Abdi M, Ahmed N, Saidu Musa S, Elehamer N, Musa M, Bolarinwa O, Dada O. Artificial intelligence for predicting and preventing adverse pregnancy outcomes addressing bias and clinical translation. Frontiers in Digital Health 2026;8 View
  3. Liu C, Su H, Ma X, Liu Z. Predictive value of routine ultrasound indicators in the second trimester for gestational diabetes mellitus: a retrospective cohort study. Frontiers in Endocrinology 2026;17 View

Conference Proceedings

  1. Iyer S, Ang E, Jiang Y, Paladugu R, Mukherjee S. 2026 ITU Kaleidoscope - AI and Frontier Technologies for Good (ITU K). Clinically-Grounded and Human-Centric Machine Learning System for Personalized Fertility Diagnostics and Early Intervention Using Modular Clinical, Imaging and Behavioral Biomarkers View