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

Clinical Information and Decision Making (1407) Machine Learning (1465) Diabetes Prevention (83) Diabetes Health Services and System Innovations (117) Gestational Diabetes (28) Tools, Programs and Algorithms (266)

Published on in Vol 24, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26634, first published .
Machine Learning Prediction Models for Gestational Diabetes Mellitus: Meta-analysis

Machine Learning Prediction Models for Gestational Diabetes Mellitus: Meta-analysis

Machine Learning Prediction Models for Gestational Diabetes Mellitus: Meta-analysis

Authors of this article:

Zheqing Zhang1 Author Orcid Image ;   Luqian Yang1 Author Orcid Image ;   Wentao Han1 Author Orcid Image ;   Yaoyu Wu1 Author Orcid Image ;   Linhui Zhang1 Author Orcid Image ;   Chun Gao1 Author Orcid Image ;   Kui Jiang1 Author Orcid Image ;   Yun Liu2, 3 Author Orcid Image ;   Huiqun Wu1 Author Orcid Image
Article Authors Cited by (29) Tweetations (9) Metrics

Journals

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  2. Jader R, Aminifar S, Ejbali R. Predictive Model for Diagnosis of Gestational Diabetes in the Kurdistan Region by a Combination of Clustering and Classification Algorithms: An Ensemble Approach. Applied Computational Intelligence and Soft Computing 2022;2022:1 View
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  6. Akano T, James C. An assessment of ensemble learning approaches and single-based machine learning algorithms for the characterization of undersaturated oil viscosity. Beni-Suef University Journal of Basic and Applied Sciences 2022;11(1) View
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  8. Arain Z, Iliodromiti S, Slabaugh G, David A, Chowdhury T. Machine learning and disease prediction in obstetrics. Current Research in Physiology 2023;6:100099 View
  9. Gokhale S, Taylor D, Gill J, Hu Y, Zeps N, Lequertier V, Teede H, Enticott J. Hospital length of stay prediction for general surgery and total knee arthroplasty admissions: Systematic review and meta-analysis of published prediction models. DIGITAL HEALTH 2023;9 View
  10. Wang J, Yin M, Wen H. Prediction performance of the machine learning model in predicting mortality risk in patients with traumatic brain injuries: a systematic review and meta-analysis. BMC Medical Informatics and Decision Making 2023;23(1) View
  11. Cubillos G, Monckeberg M, Plaza A, Morgan M, Estevez P, Choolani M, Kemp M, Illanes S, Perez C. Development of machine learning models to predict gestational diabetes risk in the first half of pregnancy. BMC Pregnancy and Childbirth 2023;23(1) View
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  13. Belsti Y, Moran L, Du L, Mousa A, De Silva K, Enticott J, Teede H. Comparison of machine learning and conventional logistic regression-based prediction models for gestational diabetes in an ethnically diverse population; the Monash GDM Machine learning model. International Journal of Medical Informatics 2023;179:105228 View
  14. Yang X, Han R, Song Y, Zhang J, Huang H, Zhang J, Wang Y, Gao L. The Mediating Role of Physical Activity Self‐Efficacy in Predicting Moderate‐Intensity Physical Activity in Pregnant People at High Risk for Gestational Diabetes. Journal of Midwifery & Women's Health 2024;69(3):403 View
  15. Wang X, He C, Wu N, Tian Y, An S, Chen W, Liu X, Zhang H, Xiong S, Liu Y, Li Q, Zhou Y, Shen X. Establishment and validation of a prediction model for gestational diabetes. Diabetes, Obesity and Metabolism 2024;26(2):663 View
  16. Chen L, Shao X, Yu P. Machine learning prediction models for diabetic kidney disease: systematic review and meta-analysis. Endocrine 2023;84(3):890 View
  17. Gou H, Song H, Tian Z, Liu Y. Prediction models for children/adolescents with obesity/overweight: A systematic review and meta-analysis. Preventive Medicine 2024;179:107823 View
  18. El-Sofany H, El-Seoud S, Karam O, Abd El-Latif Y, Taj-Eddin I, Costa G. A Proposed Technique Using Machine Learning for the Prediction of Diabetes Disease through a Mobile App. International Journal of Intelligent Systems 2024;2024:1 View
  19. Vivek Khanna V, Chadaga K, Sampathila N, Prabhu S, Chadaga P. R, Bhat D, K. S. S. Explainable artificial intelligence-driven gestational diabetes mellitus prediction using clinical and laboratory markers. Cogent Engineering 2024;11(1) View
  20. Nuthakki P, Kumar T. Machine learning-based early detection of diabetes risk factors for improved health management. Multimedia Tools and Applications 2024 View
  21. Wang J, Huang P, Hou F, Hao D, Li W, Jin H. Predicting gestational diabetes mellitus risk at 11–13 weeks’ gestation: the role of extrachromosomal circular DNA. Cardiovascular Diabetology 2024;23(1) View
  22. Kaya Y, Bütün Z, Çelik Ö, Salik E, Tahta T, Yavuz A. The early prediction of gestational diabetes mellitus by machine learning models. BMC Pregnancy and Childbirth 2024;24(1) View
  23. Yang M, Zhang L, Wang W, Huang R, He H, Zheng T, Zhang G, Fang F, Cheng J, Li F, Ouyang F, Li J, Zhang J, Luo Z. Prediction of gestational diabetes mellitus by multiple biomarkers at early gestation. BMC Pregnancy and Childbirth 2024;24(1) View
  24. Lin Y, Shi T, Kong G. Acute Kidney Injury Prognosis Prediction Using Machine Learning Methods: A Systematic Review. Kidney Medicine 2024:100936 View

Books/Policy Documents

  1. Medida L, Renugadevi R. Predicting Pregnancy Complications Through Artificial Intelligence and Machine Learning. View
  2. Priyanka , Goyal S, Bhatia R. Communication and Intelligent Systems. View
  3. Zale A, Abusamaan M, Mathioudakis N. Diabetes Digital Health, Telehealth, and Artificial Intelligence. View