An Artificial Intelligence-Based Framework for Predicting Emergency Department Overcrowding: Development and Evaluation Study.
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| Title: | An Artificial Intelligence-Based Framework for Predicting Emergency Department Overcrowding: Development and Evaluation Study. |
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| Authors: | Vural O; Department of Electrical and Computer Engineering, School of Engineering, University of Alabama at Birmingham, Birmingham, AL, United States., Ozaydin B; Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, United States.; Department of Biomedical Informatics and Data Science, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States., Aram KY; School of Business & Technology, Emporia State University, Emporia, United States., Booth J; Department of Emergency Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States., Lindsey BF; Department of Patient Throughput, University of Alabama at Birmingham Hospital, Birmingham, AL, United States., Ahmed A; Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, AL, United States.; Department of Biomedical Informatics and Data Science, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States. |
| Source: | JMIR medical informatics [JMIR Med Inform] 2025 Sep 17; Vol. 13, pp. e73960. Date of Electronic Publication: 2025 Sep 17. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: JMIR Publications Country of Publication: Canada NLM ID: 101645109 Publication Model: Electronic Cited Medium: Internet ISSN: 2291-9694 (Electronic) Linking ISSN: 22919694 NLM ISO Abbreviation: JMIR Med Inform Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2291-9694 |
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| DOI: | 10.2196/73960 |
