Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73960, first published .
An Artificial Intelligence–Based Framework for Predicting Emergency Department Overcrowding: Development and Evaluation Study

An Artificial Intelligence–Based Framework for Predicting Emergency Department Overcrowding: Development and Evaluation Study

An Artificial Intelligence–Based Framework for Predicting Emergency Department Overcrowding: Development and Evaluation Study

Orhun Vural   1 , MSc ;   Bunyamin Ozaydin   2, 3 , PhD ;   Khalid Y Aram   4 , PhD ;   James Booth   5 , MD ;   Brittany Freeman Lindsey   6 , MPA ;   Abdulaziz Ahmed   2, 3 , PhD

1 Department of Electrical and Computer Engineering, School of Engineering, University of Alabama at Birmingham, Birmingham, AL, United States

2 Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, United States

3 Department of Biomedical Informatics and Data Science, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States

4 School of Business & Technology, Emporia State University, Emporia, United States

5 Department of Emergency Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States

6 Department of Patient Throughput, University of Alabama at Birmingham Hospital, Birmingham, AL, United States

Corresponding Author:

  • Abdulaziz Ahmed, PhD
  • Department of Health Services Administration
  • School of Health Professions
  • University of Alabama at Birmingham
  • 1716 9th Ave S
  • Birmingham, AL 35233
  • United States
  • Phone: 1 205-975-1083
  • Email: aahmed2@uab.edu