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

Perioperative Infection Control and Prevention (14) Public (e)Health, Digital Epidemiology and Public Health Informatics (2217) Natural Language Processing (1223) Electronic Health Records (1651)

Published on in Vol 9 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/87896, first published .
Surgeons in blue scrubs and masks in a hospital operating room

Automated Identification of Surgical Site Infections From Electronic Medical Records: Retrospective Observational Predictive Modeling Study

Automated Identification of Surgical Site Infections From Electronic Medical Records: Retrospective Observational Predictive Modeling Study

Authors of this article:

Arjun Chakraborty1 Author Orcid Image ;   Peter Tarczy-Hornoch1, 2, 3 Author Orcid Image ;   Dustin Long4 Author Orcid Image ;   Meliha Yetisgen1 Author Orcid Image
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Arjun Chakraborty   1 , PhD ;   Peter Tarczy-Hornoch   1, 2, 3 , MD ;   Dustin Long   4 , MD ;   Meliha Yetisgen   1 , PhD

1 Department of Biomedical Informatics and Medical Education, School of Medicine, University of Washington, Rochester, MN, United States

2 Department of Pediatrics, School of Medicine, University of Washington, Seattle, WA, United States

3 Department of Computer Science and Engineering, Paul G. Allen School of Computer Science and Engineering, College of Engineering, University of Washington, Seattle, WA, United States

4 Department of Anesthesiology and Pain Medicine, School of Medicine, University of Washington, Seattle, WA, United States

Corresponding Author:

  • Arjun Chakraborty, PhD
  • Department of Biomedical Informatics and Medical Education
  • School of Medicine, University of Washington
  • 222 15th Street SW
  • Rochester, MN 55902
  • United States
  • Phone: 1 5107095904
  • Email: chakraborty.arjun@mayo.edu