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

Usability Evaluation Case Studies (220) Information Seeking, Information Needs (518) Artificial Intelligence (1665) Applications of AI (161) Machine Learning (1686) Clinical Information and Decision Making (1604) Decision Support for Health Professionals (1324)

Published on in Vol 12 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52358, first published .
Comparison of a Novel Machine Learning–Based Clinical Query Platform With Traditional Guideline Searches for Hospital Emergencies: Prospective Pilot Study of User Experience and Time Efficiency

Comparison of a Novel Machine Learning–Based Clinical Query Platform With Traditional Guideline Searches for Hospital Emergencies: Prospective Pilot Study of User Experience and Time Efficiency

Comparison of a Novel Machine Learning–Based Clinical Query Platform With Traditional Guideline Searches for Hospital Emergencies: Prospective Pilot Study of User Experience and Time Efficiency

Authors of this article:

Hamza Ejaz1 Author Orcid Image ;   Hon Lung Keith Tsui2 Author Orcid Image ;   Mehul Patel2 Author Orcid Image ;   Luis Rafael Ulloa Paredes2 Author Orcid Image ;   Ellen Knights1 Author Orcid Image ;   Shah Bakht Aftab3 Author Orcid Image ;   Christian Peter Subbe4 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Hamza Ejaz   1 , MD ;   Hon Lung Keith Tsui   2 * , MD ;   Mehul Patel   2 , MD ;   Luis Rafael Ulloa Paredes   2 , MSc ;   Ellen Knights   1 , BSc ;   Shah Bakht Aftab   3 * , MD ;   Christian Peter Subbe   4 * , Dr med

1 Ysbyty Gwynedd, Clinical School, Clinical Research Office, Bangor, United Kingdom

2 Medwise.ai Ltd, Leeds, United Kingdom

3 Russells Hall Hospital, Dudley, United Kingdom

4 North Wales Medical School, Bangor University, Bangor, United Kingdom

*these authors contributed equally

Corresponding Author:

  • Christian Peter Subbe, Dr med
  • North Wales Medical School
  • Bangor University
  • Brigantia Building
  • Bangor, LL57 2AS
  • United Kingdom
  • Phone: 44 7771922890
  • Email: c.subbe@bangor.ac.uk