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

Ontologies, Classifications, and Coding (227) Electronic Health Records (971) Secondary Use of Clinical Data for Research and Surveillance (326) Natural Language Processing (650) Machine Learning (1401) Big Data (220) Tools, Programs and Algorithms (246)

Published on in Vol 10, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/39057, first published .
Standard Vocabularies to Improve Machine Learning Model Transferability With Electronic Health Record Data: Retrospective Cohort Study Using Health Care–Associated Infection

Standard Vocabularies to Improve Machine Learning Model Transferability With Electronic Health Record Data: Retrospective Cohort Study Using Health Care–Associated Infection

Standard Vocabularies to Improve Machine Learning Model Transferability With Electronic Health Record Data: Retrospective Cohort Study Using Health Care–Associated Infection

Authors of this article:

Amber C Kiser1 Author Orcid Image ;   Karen Eilbeck1 Author Orcid Image ;   Jeffrey P Ferraro2 Author Orcid Image ;   David E Skarda3, 4 Author Orcid Image ;   Matthew H Samore2, 5 Author Orcid Image ;   Brian Bucher1, 4 Author Orcid Image
Article Authors Cited by (1) Tweetations (10) Metrics

Amber C Kiser   1 , BS ;   Karen Eilbeck   1 , MSc, PhD ;   Jeffrey P Ferraro   2 , PhD ;   David E Skarda   3, 4 , MD ;   Matthew H Samore   2, 5 , MD ;   Brian Bucher   1, 4 , MS, MD

1 Department of Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, United States

2 Department of Medicine, School of Medicine, University of Utah, Salt Lake City, UT, United States

3 Center for Value-Based Surgery, Intermountain Healthcare, Salt Lake City, UT, United States

4 Department of Surgery, School of Medicine, University of Utah, Salt Lake City, UT, United States

5 Informatics, Decision-Enhancement and Analytic Sciences Center 2.0, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, UT, United States

Corresponding Author:

  • Amber C Kiser, BS
  • Department of Biomedical Informatics
  • School of Medicine
  • University of Utah
  • 421 Wakara Way
  • Suite 140
  • Salt Lake City, UT, 84108
  • United States
  • Phone: 1 801-581-4080
  • Email: amber.kiser@utah.edu