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

Electronic Health Records (1444) Clinical Information and Decision Making (2184) Decision Support for Health Professionals (1729) Pathology and Laboratory Medicine (41) Secondary Use of Clinical Data for Research and Surveillance (515) Machine Learning (2345)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/85255, first published .
Computer monitor displaying scientific data and graphs in a laboratory setting.

Predicting Laboratory Test Ordering in Emergency Departments Using Integrated Structured and Unstructured Electronic Health Records: Machine Learning Study

Predicting Laboratory Test Ordering in Emergency Departments Using Integrated Structured and Unstructured Electronic Health Records: Machine Learning Study

Authors of this article:

Xingyu Zhang1 Author Orcid Image ;   Haipeng Ling2 Author Orcid Image ;   Xin Zhang3 Author Orcid Image ;   Anao Zhang4 Author Orcid Image
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Xingyu Zhang   1 * , MSc, PhD ;   Haipeng Ling   2 , MS ;   Xin Zhang   3 , MSc ;   Anao Zhang   4 * , MSW, PhD

1 Department of Communication Science and Disorders, School of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, United States

2 Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, United States

3 Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States

4 Center for Interdisciplinary Psychosocial Oncology and Palliative Care Research and Practice, School of Social Work, University of Washington, Seattle, WA, United States

*these authors contributed equally

Corresponding Author:

  • Anao Zhang, MSW, PhD
  • Center for Interdisciplinary Psychosocial Oncology and Palliative Care Research and Practice
  • School of Social Work, University of Washington
  • 4101 15th Avenue NE
  • Seattle, WA 98105
  • United States
  • Phone: 1 206-543-8867
  • Email: anaoz@uw.edu