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Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/84454, first published .
Doctor performing an ultrasound on a pregnant woman, with a fetal image on screen.

Machine Learning to Identify Point-of-Care Ultrasound and Evaluate Standardized Documentation: Retrospective Operational Cohort Study

Machine Learning to Identify Point-of-Care Ultrasound and Evaluate Standardized Documentation: Retrospective Operational Cohort Study

Kevin Nguyen   1 , MS, MD ;   Zewen Wu   1 , MS ;   Chu-An Tsai   1 , MS ;   John Vandervest   1 , MS ;   D’Anna Lammers   2 , CPC, BS ;   Ruth Cassidy   1 , MS ;   Zachary Murphy   1 , MD, MSE ;   Balaji Pandian   3 , MD, MBA ;   Maya M Hammoud   2 , MD, MBA ;   Jennifer Collin   2 , MD ;   Roger Smith   2 , MD ;   Rosalyn Maben-Feaster   2 , MD, MPH ;   Amy Kaufman Eddy   2 , MPH ;   Michael L Burns   1 , MD, PhD

1 Department of Anesthesiology, University of Michigan, Ann Arbor, MI, United States

2 Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, United States

3 Department of Anesthesiology, Weill Cornell Medicine, New York, NY, United States

Corresponding Author:

  • Michael L Burns, MD, PhD
  • Department of Anesthesiology
  • University of Michigan
  • 1500 E. Medical Center Drive
  • Ann Arbor, MI 48109
  • United States
  • Phone: 1 734-936-4280
  • Email: mlburns@med.umich.edu