Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53091, first published .
Use of Machine Learning for Early Detection of Maternal Cardiovascular Conditions: Retrospective Study Using Electronic Health Record Data

Use of Machine Learning for Early Detection of Maternal Cardiovascular Conditions: Retrospective Study Using Electronic Health Record Data

Use of Machine Learning for Early Detection of Maternal Cardiovascular Conditions: Retrospective Study Using Electronic Health Record Data

Journals

  1. Sliti H, Rasheed A, Tripathi S, Jesso S, Madathil S. Incorporating machine learning and statistical methods to address maternal healthcare disparities in US: A systematic review. International Journal of Medical Informatics 2025;200:105918 View
  2. Jafree S, Mubasher M. Predicting high risk pregnancies in Pakistan- a demographic assessment using predictive machine learning. Quality & Quantity 2025;59(6):4927 View
  3. Turekulova A, Dzhardemaliyeva N, Mereke A, Kulimbet M. Maternal Disorders Associated with Morbidity and Mortality in a Metropolis of Kazakhstan. Clinics and Practice 2025;15(6):108 View
  4. Zapata R, Tolani T, Reich R, Beneteau S, Ali H, Kolli T, Rechdan M, Brinkley L, Himadi M, Louis-Jacques A, Modave F, Smith S, Wen T, Shenkman E, Lemas D. AI in Hypertensive Disorders of Pregnancy: Review. American Journal of Hypertension 2025 View
  5. Ngepah N, Saba C, Mouteyica A, Ohonba A. The impact of artificial intelligence (AI) on maternal mortality: evidence from global, developed and developing countries. Globalization and Health 2025;21(1) View
  6. Wander G, Hopkins T, Scatola A, Ruby G, Johnson M, Mehta-Lee S, Glicksberg B, Krittanawong C. The role of artificial intelligence in cardio-obstetrics – current applications and future directions. Trends in Cardiovascular Medicine 2025 View