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

Artificial Intelligence (122) Usability of Apps and User Perceptions of mHealth (902) Machine Learning (1401) Artificial Intelligence (1216) Clinical Information and Decision Making (1340)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46487, first published .
Artificial Intelligence in Health Care—Understanding Patient Information Needs and Designing Comprehensible Transparency: Qualitative Study

Artificial Intelligence in Health Care—Understanding Patient Information Needs and Designing Comprehensible Transparency: Qualitative Study

Artificial Intelligence in Health Care—Understanding Patient Information Needs and Designing Comprehensible Transparency: Qualitative Study

Authors of this article:

Renee Robinson1 Author Orcid Image ;   Cara Liday2 Author Orcid Image ;   Sarah Lee3 Author Orcid Image ;   Ishan C Williams4 Author Orcid Image ;   Melanie Wright3 Author Orcid Image ;   Sungjoon An3 Author Orcid Image ;   Elaine Nguyen3 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Journals

  1. Jairoun A, Al-Hemyari S, Shahwan M, Al-Qirim T, Shahwan M. Benefit–Risk Assessment of ChatGPT Applications in the Field of Diabetes and Metabolic Illnesses: A Qualitative Study. Clinical Medicine Insights: Endocrinology and Diabetes 2024;17 View