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Digital Health Reviews (3656) Clinical Information and Decision Making (3693) Reviews in Medical Informatics (482) Machine Learning (3165) Artificial Intelligence (4754) Precision Medicine (434)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78714, first published .
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Machine Learning Prediction Models for Preeclampsia: Systematic Review and Meta-Analysis

Machine Learning Prediction Models for Preeclampsia: Systematic Review and Meta-Analysis

Authors of this article:

Lu Liu1, 2 Author Orcid Image ;   Qixuan Zhu3 Author Orcid Image ;   Yichi Zong2 Author Orcid Image ;   Xueyuan Chen2 Author Orcid Image ;   Wei Zhang2 Author Orcid Image ;   Jun Wang4 Author Orcid Image
Article Authors Cited by (7) Tweetations (2) Metrics

Journals

  1. Ismail M. The economic imperative of artificial intelligence in maternal and neonatal health: a review of evaluation benefits, frameworks, challenges, future perspectives, and limitations. Cost Effectiveness and Resource Allocation 2026;24(1) View
  2. Sivasankari K, Mohan S. Artificial Intelligence in Obstetrics and Gynecology Nursing: Clinical, Educational, and Ethical Perspectives. Cureus 2026 View
  3. Andonotopo W, Pramono M, Dewantiningrum J, Bachnas M, Prabowo W, Sanjaya I, Wiradnyana A, Kusuma A, Gumilar K, Akbar M, Darmawan E, Suryawan A, Putra R, Rahardjo T, Anwar A, Aldiansyah D, Nugraha L, Andanaputra W, Dharma W. Bioinformatics for Multimodal Precision Pregnancy: A Systematic Review of Causal, Foundation, and Privacy-Preserving Models for Predicting Pregnancy Complications and Fetal Health Outcomes. Telangana Journal of IMA 2026;6(1):24 View
  4. Perez M, Falconi L, Intriago-Pazmiño M, Bastidas-Fuertes A, Benavides J, Fuertes-Arévalo R. A Machine Learning Framework for Preeclampsia Prediction at Isidro Ayora Hospital, Ecuador. Diagnostics 2026;16(14):2147 View
  5. Alruwaili M, Paul-Chima U. Equity-centred, nurse-led implementation of artificial intelligence in community maternal and child health nursing: a conceptual framework for low-resource settings. Frontiers in Public Health 2026;14 View
  6. Guo J, Bao C, Gong L, Zhang Z. Comparing machine learning models and traditional approaches for predicting obstructive coronary artery disease: a systematic review and meta-analysis. Frontiers in Cardiovascular Medicine 2026;13 View
  7. Barada S, Selvanambi R. Artificial intelligence for early prediction of gestational diabetes mellitus and preeclampsia: a systematic review of machine learning models and clinical decision support systems. Frontiers in Artificial Intelligence 2026;9 View