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

Applications of AI (905) Clinical Informatics (2205) Clinical Information and Decision Making (3629) Organizational Issues (266) Decision Support for Health Professionals (2180) Machine Learning (3113)

Published on in Vol 5 (2026)

This is a member publication of Eindhoven University of Technology

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80448, first published .
Medical team wheels patient on gurney down hospital hallway

Evaluating an AI Decision Support System for the Emergency Department: Retrospective Study

Evaluating an AI Decision Support System for the Emergency Department: Retrospective Study

Authors of this article:

Yvette Van Der Haas1, 2 Author Orcid Image ;   Wiesje Roskamp2 Author Orcid Image ;   Lidwina Elisabeth Maria Chang-Willems2 Author Orcid Image ;   Boudewijn van Dongen1 Author Orcid Image ;   Swetta Jansen2 Author Orcid Image ;   Annemarie de Jong2 Author Orcid Image ;   Renata Medeiros de Carvalho1 Author Orcid Image ;   Dorien Melman2 Author Orcid Image ;   Arjan van de Merwe2 ;   Marieke Bastian-Sanders2 Author Orcid Image ;   Bart Overbeek2 Author Orcid Image ;   Rogier Leendert Charles Plas2 Author Orcid Image ;   Marleen Vreeburg2 Author Orcid Image ;   Thomas van Dijk2 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Aydın Ö, Tatlı M. From accuracy to impact: Bridging the methodological gap in artificial intelligence for emergency department care. The American Journal of Emergency Medicine 2026;105:193 View
  2. Dinh M, Corbett E, Ngo T, Salmon E, Khan S, Pethani F, Moore N, Koprinska I. The Sydney Triage to Admission Risk Tool With Artificial Intelligence (START‐AI) to Support Decision Making in Emergency Departments: Model Explainability and Feature Importance Analysis. Emergency Medicine Australasia 2026;38(4) View