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

Formative Evaluation of Digital Health Interventions (2410) Clinical Information and Decision Making (1407) Adoption and Change Management of eHealth Systems (712) Decision Support for Health Professionals (1185) Artificial Intelligence (1371)

Published on in Vol 6, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36501, first published .
Acceptance, Barriers, and Facilitators to Implementing Artificial Intelligence–Based Decision Support Systems in Emergency Departments: Quantitative and Qualitative Evaluation

Acceptance, Barriers, and Facilitators to Implementing Artificial Intelligence–Based Decision Support Systems in Emergency Departments: Quantitative and Qualitative Evaluation

Acceptance, Barriers, and Facilitators to Implementing Artificial Intelligence–Based Decision Support Systems in Emergency Departments: Quantitative and Qualitative Evaluation

Authors of this article:

Ryo Fujimori1, 2 Author Orcid Image ;   Keibun Liu2, 3 Author Orcid Image ;   Shoko Soeno2, 4 Author Orcid Image ;   Hiromu Naraba2, 5 Author Orcid Image ;   Kentaro Ogura1, 2 Author Orcid Image ;   Konan Hara2, 6 Author Orcid Image ;   Tomohiro Sonoo2, 5 Author Orcid Image ;   Takayuki Ogura7 Author Orcid Image ;   Kensuke Nakamura5 Author Orcid Image ;   Tadahiro Goto2 Author Orcid Image
Article Authors Cited by (35) Tweetations (18) Metrics

Journals

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  18. Giddings R, Joseph A, Callender T, Janes S, van der Schaar M, Sheringham J, Navani N. Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review. The Lancet Digital Health 2024;6(2):e131 View
  19. Rony M, Kayesh I, Bala S, Akter F, Parvin M. Artificial intelligence in future nursing care: Exploring perspectives of nursing professionals - A descriptive qualitative study. Heliyon 2024;10(4):e25718 View
  20. Dingel J, Kleine A, Cecil J, Sigl A, Lermer E, Gaube S. Predictors of Health Care Practitioners’ Intention to Use AI-Enabled Clinical Decision Support Systems: Meta-Analysis Based on the Unified Theory of Acceptance and Use of Technology. Journal of Medical Internet Research 2024;26:e57224 View
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