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

Quality Improvement (260) Clinical Information and Decision Making (1434) Decision Support for Health Professionals (1210) Electronic Health Records (1068) Machine Learning (1501) Data Science (278) Clinical Informatics (1050) Cost-Effectiveness and Economics (259)

Published on in Vol 10, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37239, first published .
A Framework for Modeling and Interpreting Patient Subgroups Applied to Hospital Readmission: Visual Analytical Approach

A Framework for Modeling and Interpreting Patient Subgroups Applied to Hospital Readmission: Visual Analytical Approach

A Framework for Modeling and Interpreting Patient Subgroups Applied to Hospital Readmission: Visual Analytical Approach

Authors of this article:

Suresh K Bhavnani1 Author Orcid Image ;   Weibin Zhang1 Author Orcid Image ;   Shyam Visweswaran2 Author Orcid Image ;   Mukaila Raji3 Author Orcid Image ;   Yong-Fang Kuo1 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Suresh K Bhavnani   1 , MArch, PhD ;   Weibin Zhang   1 , PhD ;   Shyam Visweswaran   2 , MD, PhD ;   Mukaila Raji   3 , MSc, MD ;   Yong-Fang Kuo   1 , PhD

1 School of Public and Population Health, University of Texas Medical Branch, Galveston, TX, United States

2 Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, United States

3 Division of Geriatric Medicine, Department of Internal Medicine, University of Texas Medical Branch, Galveston, TX, United States

Corresponding Author:

  • Suresh K Bhavnani, MArch, PhD
  • School of Public and Population Health
  • University of Texas Medical Branch
  • Institute for Translational Sciences
  • 301 University Blvd.
  • Galveston, TX, 77555-0129
  • United States
  • Phone: 1 (409) 772-1928
  • Email: subhavna@utmb.edu