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

Cognition and Information Processing in Human Factors Research (28) Clinical Information and Decision Making (1915) Safety and Error Prevention in Health (240) ePrescribing and Innovations in Pharmacies (84) Artificial Intelligence (2129) Simulation (164) Quality/Credibility of eHealth Information and Trust Issues (654) Design and Usability of Medical Devices (141)

Published on in Vol 12 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60273, first published .
The Effects of Presenting AI Uncertainty Information on Pharmacists’ Trust in Automated Pill Recognition Technology: Exploratory Mixed Subjects Study

The Effects of Presenting AI Uncertainty Information on Pharmacists’ Trust in Automated Pill Recognition Technology: Exploratory Mixed Subjects Study

The Effects of Presenting AI Uncertainty Information on Pharmacists’ Trust in Automated Pill Recognition Technology: Exploratory Mixed Subjects Study

Authors of this article:

Jin Yong Kim1 Author Orcid Image ;   Vincent D Marshall2 Author Orcid Image ;   Brigid Rowell2 Author Orcid Image ;   Qiyuan Chen1 Author Orcid Image ;   Yifan Zheng2 Author Orcid Image ;   John D Lee3 Author Orcid Image ;   Raed Al Kontar1 Author Orcid Image ;   Corey Lester2 Author Orcid Image ;   Xi Jessie Yang1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Jin Yong Kim   1 , BSE ;   Vincent D Marshall   2 , MS ;   Brigid Rowell   2 , MA ;   Qiyuan Chen   1 , MSE ;   Yifan Zheng   2 , PharmD ;   John D Lee   3 , PhD ;   Raed Al Kontar   1 , PhD ;   Corey Lester   2 , PharmD, PhD ;   Xi Jessie Yang   1 , PhD

1 Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, United States

2 College of Pharmacy, University of Michigan, Ann Arbor, MI, United States

3 Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, MI, United States

Corresponding Author:

  • Xi Jessie Yang, PhD
  • Industrial and Operations Engineering
  • University of Michigan
  • 1640 IOE
  • 1205 Beal Avenue
  • Ann Arbor, MI 48105
  • United States
  • Phone: 1 7347630541
  • Email: xijyang@umich.edu