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

Theme Issue 2024: Machine Learning-Based Predictive Models Using Genomic Data (5) Clinical Information and Decision Making (1434) Machine Learning (1501) Development and Evaluation of Research Methods, Instruments and Tools (511) Artificial Intelligence (1421) Decision Support for Health Professionals (1210) Bioinformatics, genomics, tools and databases (18)

Published on in Vol 5 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52059, first published .
Machine Learning Models for Prediction of Maternal Hemorrhage and Transfusion: Model Development Study

Machine Learning Models for Prediction of Maternal Hemorrhage and Transfusion: Model Development Study

Machine Learning Models for Prediction of Maternal Hemorrhage and Transfusion: Model Development Study

Authors of this article:

Homa Khorrami Ahmadzia1, 2 Author Orcid Image ;   Alexa C Dzienny3 Author Orcid Image ;   Mike Bopf4 Author Orcid Image ;   Jaclyn M Phillips1 Author Orcid Image ;   Jerome Jeffrey Federspiel5 Author Orcid Image ;   Richard Amdur6 Author Orcid Image ;   Madeline Murguia Rice7 Author Orcid Image ;   Laritza Rodriguez4 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Homa Khorrami Ahmadzia   1, 2 * , MD, MPH ;   Alexa C Dzienny   3 , BS ;   Mike Bopf   4 * , MS ;   Jaclyn M Phillips   1 , MD ;   Jerome Jeffrey Federspiel   5 * , MD, PhD ;   Richard Amdur   6 , PhD ;   Madeline Murguia Rice   7 , PhD ;   Laritza Rodriguez   4 , MD, PhD

1 Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, George Washington University, Washington, DC, United States

2 Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Inova Health System, Falls Church, VA, United States

3 The George Washington University School of Medicine and Health Sciences,, Washington DC, DC, United States

4 Lister Hill National Center for Biomedical Communications, U.S. National Library of Medicine, Bethesda, MD, United States

5 Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Duke University, Durham, NC, United States

6 Medical Faculty Associates, The George Washington University School of Medicine and Health Sciences, Washington, DC, United States

7 George Washington University Biostatistics Center, Washington, DC, United States

*these authors contributed equally

Corresponding Author:

  • Homa Khorrami Ahmadzia, MD, MPH
  • Division of Maternal-Fetal Medicine
  • Department of Obstetrics and Gynecology
  • Inova Health System
  • 3300 Gallows Road
  • Falls Church, VA, 22042
  • United States
  • Phone: 1 571-472-0920
  • Email: homa.ahmadzia@inova.org