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

Clinical Information and Decision Making (1438) Registered Report (579) Machine Learning (1505) Pulmonology, COPD (145) Decision Support for Health Professionals (1211) Clinical Informatics (1050) Tools, Programs and Algorithms (275)

Published on in Vol 24, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28953, first published .
Developing a Machine Learning Model to Predict Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study

Developing a Machine Learning Model to Predict Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study

Developing a Machine Learning Model to Predict Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study

Authors of this article:

Siyang Zeng1 Author Orcid Image ;   Mehrdad Arjomandi2, 3 Author Orcid Image ;   Yao Tong1 Author Orcid Image ;   Zachary C Liao1 Author Orcid Image ;   Gang Luo1 Author Orcid Image
Article Authors Cited by (14) Tweetations (14) Metrics

Siyang Zeng   1 , MS ;   Mehrdad Arjomandi   2, 3 , MD ;   Yao Tong   1 , MSc ;   Zachary C Liao   1 , MPH, MD ;   Gang Luo   1 , DPhil

1 Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, United States

2 Medical Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, United States

3 Department of Medicine, University of California, San Francisco, CA, United States

Corresponding Author:

  • Gang Luo, DPhil
  • Department of Biomedical Informatics and Medical Education
  • University of Washington
  • UW Medicine South Lake Union, 850 Republican Street, Building C, Box 358047
  • Seattle, WA, 98195
  • United States
  • Phone: 1 206 221 4596
  • Fax: 1 206 221 2671
  • Email: gangluo@cs.wisc.edu