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

Digital Health Reviews (3933) Clinical Information and Decision Making (3967) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (2466) Diabetes (355) Glucose Tracking and Self-Monitoring of Blood Glucose (253) Diabetes Self-Management (740) Machine Learning (3391) Artificial Intelligence (5120)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/100653, first published .
Man checks blood pressure with digital monitor next to notebook with "Diabetes" written

Machine Learning Models for Glycemic Prediction in Type 1 and Type 2 Diabetes: Systematic Review and Meta-Analysis

Machine Learning Models for Glycemic Prediction in Type 1 and Type 2 Diabetes: Systematic Review and Meta-Analysis

Authors of this article:

Haoran Yang1, 2 Author Orcid Image ;   Diliyaer Abudukeremu2 Author Orcid Image ;   Yuhan Shi3 Author Orcid Image ;   Li Fang4, 5 Author Orcid Image ;   Lei Li1 Author Orcid Image ;   Wenzheng Gu6 Author Orcid Image ;   Yunqi Jia6 Author Orcid Image ;   Rongfang He1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Haoran Yang   1, 2 * ;   Diliyaer Abudukeremu   2 * , BMed ;   Yuhan Shi   3 ;   Li Fang   4, 5 ;   Lei Li   1 , MD ;   Wenzheng Gu   6 , MMed ;   Yunqi Jia   6 , MMed ;   Rongfang He   1 , MD

1 Department of Pathology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China

2 Tianjin Medical University Cancer Institute and Hospital, Tianjin, China

3 The Second Clinical College of Tianjin Medical University Second Hospital, Tianjin, China

4 Meiwan Community Health Service Station (Municipal Party Committee Clinic), Yongzhou, China

5 Cai Township Health Center, Yongzhou, China

6 First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, National Clinical Research Center for Chinese Medicine, Tianjin, China

*these authors contributed equally

Corresponding Author:

  • Rongfang He, MD
  • Department of Pathology
  • The First Affiliated Hospital, Hengyang Medical School, University of South China
  • No. 69, Chuanshan Road
  • Hengyang 421001
  • China
  • Phone: +86 18773464745
  • Email: herongfang2019@fsyy.usc.edu.cn