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

Digital Health Reviews (1725) Machine Learning (2077) Electronic Health Records (1319) Clinical Informatics (1325) Obstetrics, Gynecology, and Reproductive Medicine (329) Pregnancy Information, Education and Lifestyle Interventions (401)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68225, first published .
Machine Learning Models to Predict Risk of Maternal Morbidity and Mortality From Electronic Medical Record Data: Scoping Review

Machine Learning Models to Predict Risk of Maternal Morbidity and Mortality From Electronic Medical Record Data: Scoping Review

Machine Learning Models to Predict Risk of Maternal Morbidity and Mortality From Electronic Medical Record Data: Scoping Review

Authors of this article:

Lavanya Vasudevan1, 2 Author Orcid Image ;   Mohammad Golam Kibria3 Author Orcid Image ;   Lauren M Kucirka4, 5 Author Orcid Image ;   Karl Shieh4 Author Orcid Image ;   Mian Wei6 Author Orcid Image ;   Safoora Masoumi3 Author Orcid Image ;   Subha Balasubramanian7 Author Orcid Image ;   Ashley Victor3 Author Orcid Image ;   Jamie L Conklin8 Author Orcid Image ;   Metin Nafi Gurcan9 Author Orcid Image ;   Alison M Stuebe4, 10 Author Orcid Image ;   David Page6 Author Orcid Image
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Journals

  1. Carvalho e Silva M, Figueiredo Delgado A, Carvalho e Silva F. Machine learning identification of factors associated with exclusive breastfeeding in Brazilian infants: Cross-sectional analysis of the ENANI-2019 survey. International Journal of Medical Informatics 2026;206:106126 View