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

Design and Usability of Medical Devices (103) Clinical Information and Decision Making (1434) Tools, Programs and Algorithms (275) Machine Learning (1501) Artificial Intelligence (1421) User-centred Design Case Studies (602) Usability of Apps and User Perceptions of mHealth (993) Quality/Credibility of eHealth Information and Trust Issues (544)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/56924, first published .
The Impact of Information Relevancy and Interactivity on Intensivists’ Trust in a Machine Learning–Based Bacteremia Prediction System: Simulation Study

The Impact of Information Relevancy and Interactivity on Intensivists’ Trust in a Machine Learning–Based Bacteremia Prediction System: Simulation Study

The Impact of Information Relevancy and Interactivity on Intensivists’ Trust in a Machine Learning–Based Bacteremia Prediction System: Simulation Study

Authors of this article:

Omer Katzburg1 Author Orcid Image ;   Michael Roimi2 Author Orcid Image ;   Amit Frenkel3 Author Orcid Image ;   Roy Ilan2 Author Orcid Image ;   Yuval Bitan1 Author Orcid Image
Article Authors Cited by Tweetations (1) Metrics

Omer Katzburg   1 , MSc ;   Michael Roimi   2 , MD ;   Amit Frenkel   3 , MD ;   Roy Ilan   2 , MD ;   Yuval Bitan   1 , PhD

1 Department of Health Policy and Management, Ben-Gurion University of the Negev, Be'er Sheva, Israel

2 General Intensive Care Unit, Rambam Medical Center, Haifa, Israel

3 General Intensive Care Unit, Soroka Medical Center, Be'er Sheva, Israel

Corresponding Author:

  • Yuval Bitan, PhD
  • Department of Health Policy and Management
  • Ben-Gurion University of the Negev
  • 1 Ben Gurion Blvd
  • Be'er Sheva, 8410501
  • Israel
  • Phone: 972 546543210
  • Email: yuval@bitan.net