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

Machine Learning (1996) Clinical Information and Decision Making (1828) Decision Support for Health Professionals (1486)

Published on in Vol 7, No 1 (2019): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12591, first published .
Predicting Appropriate Hospital Admission of Emergency Department Patients with Bronchiolitis: Secondary Analysis

Predicting Appropriate Hospital Admission of Emergency Department Patients with Bronchiolitis: Secondary Analysis

Predicting Appropriate Hospital Admission of Emergency Department Patients with Bronchiolitis: Secondary Analysis

Authors of this article:

Gang Luo1 Author Orcid Image ;   Bryan L Stone2 Author Orcid Image ;   Flory L Nkoy2 Author Orcid Image ;   Shan He3 Author Orcid Image ;   Michael D Johnson2 Author Orcid Image
Article Authors Cited by (11) Tweetations (6) Metrics

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  2. Saberinia A, Vafaei A, Kashani P. A narrative review on the management of Acute Heart Failure in Emergency Medicine Department. European Journal of Translational Myology 2020;30(1):171 View
  3. Martinez-Garcia A, Naranjo-Saucedo A, Rivas J, Romero Tabares A, Marín Cassinello A, Andrés-Martín A, Sánchez Laguna F, Villegas R, Pérez León F, Moreno Conde J, Parra Calderón C. A Clinical Decision Support System (KNOWBED) to Integrate Scientific Knowledge at the Bedside: Development and Evaluation Study. JMIR Medical Informatics 2021;9(3):e13182 View
  4. Bizune D, Tsay S, Palms D, King L, Bartoces M, Link-Gelles R, Fleming-Dutra K, Hicks L. Regional Variation in Outpatient Antibiotic Prescribing for Acute Respiratory Tract Infections in a Commercially Insured Population, United States, 2017. Open Forum Infectious Diseases 2023;10(2) View
  5. Eggli Y, Halfon P, Piaget-Rossel R, Bischoff T. Measuring medically unjustified hospitalizations in Switzerland. BMC Health Services Research 2022;22(1) View
  6. El-Bouri R, Taylor T, Youssef A, Zhu T, Clifton D. Machine learning in patient flow: a review. Progress in Biomedical Engineering 2021;3(2):022002 View
  7. Tso C, Lam C, Calvert J, Mao Q. Machine learning early prediction of respiratory syncytial virus in pediatric hospitalized patients. Frontiers in Pediatrics 2022;10 View
  8. Chekani F, Zhu Z, Khandker R, Ai J, Meng W, Holler E, Dexter P, Boustani M, Ben Miled Z. Modeling acute care utilization: practical implications for insomnia patients. Scientific Reports 2023;13(1) View
  9. Ahmed A, Aram K, Tutun S, Delen D. A study of “left against medical advice” emergency department patients: an optimized explainable artificial intelligence framework. Health Care Management Science 2024;27(4):485 View
  10. Abugroun A, Awadalla S, Singh S, Fang M. Development of an emergency department triage tool to predict admission or discharge for older adults. International Journal of Emergency Medicine 2025;18(1) View
  11. Kuo K, Chang C. A meta-analysis of the diagnostic test accuracy of artificial intelligence predicting emergency department dispositions. BMC Medical Informatics and Decision Making 2025;25(1) View