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

Theme Issue (2023): Generative & Multimodal AI in Digital Cardiovascular Medicine (6) Clinical Informatics (1131) Clinical Information and Decision Making (1603) Artificial Intelligence (1665) Machine Learning (1685) Precision Medicine (94) Cardiology (188) Electronic Health Records (1154) Pregnancy Information, Education and Lifestyle Interventions (342)

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

Authors of this article:

Nawar Shara1, 2 Author Orcid Image ;   Roxanne Mirabal-Beltran3 Author Orcid Image ;   Bethany Talmadge4 Author Orcid Image ;   Noor Falah1 Author Orcid Image ;   Maryam Ahmad1 Author Orcid Image ;   Ramon Dempers4 Author Orcid Image ;   Samantha Crovatt4 Author Orcid Image ;   Steven Eisenberg4 Author Orcid Image ;   Kelley Anderson3 Author Orcid Image
Article Authors Cited by (1) Tweetations (7) Metrics

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