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

Design and Usability of Medical Devices (141) Clinical Information and Decision Making (1915) Tools, Programs and Algorithms (376) Machine Learning (2076) Artificial Intelligence (2129) User-Centered Design Case Studies (713) Usability of Apps and User Perceptions of mHealth (1188) Quality/Credibility of eHealth Information and Trust Issues (654)

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 (2) Tweetations (1) Metrics

Journals

  1. Shamszare H, Chaudhry Z, Berenji M, Choudhury A. Conceptualizing Clinicians’ Trust in Artificial Intelligence as a Function of Their Expertise, Workload, Patient Outcome, Diagnosis Difficulty, and AI Accuracy: A Systems Thinking Approach. IEEE Access 2025;13:119601 View

Conference Proceedings

  1. Song X. Proceeding of the 2024 International Conference on Artificial Intelligence and Future Education. Design of a simulation learning system for ideological and political courses in universities based on VR technology View