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

Clinical Informatics (1050) Obstetrics, Gynecology, and Reproductive Medicine (237) Theme Issue 2022: Reproductive Informatics (55) Tx to JMIR Medical Informatics awaiting EIC consent (1) Midwifery, Nurse-midwifery and Care for Pregnant or New Mothers (60)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48997, first published .
Five-Feature Models to Predict Preeclampsia Onset Time From Electronic Health Record Data: Development and Validation Study

Five-Feature Models to Predict Preeclampsia Onset Time From Electronic Health Record Data: Development and Validation Study

Five-Feature Models to Predict Preeclampsia Onset Time From Electronic Health Record Data: Development and Validation Study

Authors of this article:

Hailey K Ballard1, 2 Author Orcid Image ;   Xiaotong Yang1 Author Orcid Image ;   Aditya D Mahadevan3, 4 Author Orcid Image ;   Dominick J Lemas2, 3, 5 Author Orcid Image ;   Lana X Garmire1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Hailey K Ballard   1, 2 , BS ;   Xiaotong Yang   1 , MS ;   Aditya D Mahadevan   3, 4 , BS ;   Dominick J Lemas   2, 3, 5 , PhD ;   Lana X Garmire   1 , PhD

1 Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, United States

2 Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, United States

3 Center for Research in Perinatal Outcomes, University of Florida, Gainesville, FL, United States

4 Department of Physiology and Aging, University of Florida, Gainesville, FL, United States

5 Department of Obstetrics & Gynecology, University of Florida, Gainesville, FL, United States

Corresponding Author:

  • Lana X Garmire, PhD
  • Department of Computational Medicine and Bioinformatics
  • University of Michigan Medical School
  • Room 3366, Building 520, NCRC
  • 1600 Huron Parkway
  • Ann Arbor, MI, 48105
  • United States
  • Phone: 1 734-615-0514
  • Email: lgarmire@gmail.com