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

Design and Usability of Clinical Software and EHRs (242) Artificial Intelligence (1192) Decision Support for Health Professionals (1132) Clinical Information and Decision Making (1320) Usability of Apps and User Perceptions of mHealth (894) User Needs and Competencies (271) Clinical Informatics (908)

Published on in Vol 9, No 1 (2022): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24680, first published .
Acceptance of the Use of Artificial Intelligence in Medicine Among Japan’s Doctors and the Public: A Questionnaire Survey

Acceptance of the Use of Artificial Intelligence in Medicine Among Japan’s Doctors and the Public: A Questionnaire Survey

Acceptance of the Use of Artificial Intelligence in Medicine Among Japan’s Doctors and the Public: A Questionnaire Survey

Authors of this article:

Honoka Tamori1 Author Orcid Image ;   Hiroko Yamashina2, 3 Author Orcid Image ;   Masami Mukai1, 4 Author Orcid Image ;   Yasuhiro Morii5 Author Orcid Image ;   Teppei Suzuki2, 6 Author Orcid Image ;   Katsuhiko Ogasawara2 Author Orcid Image
Article Authors Cited by (13) Tweetations (3) Metrics

Journals

  1. Kloka J, Holtmann S, Nürenberg-Goloub E, Piekarski F, Zacharowski K, Friedrichson B. Expectations of Anesthesiology and Intensive Care Professionals Toward Artificial Intelligence: Observational Study. JMIR Formative Research 2023;7:e43896 View
  2. Farah L, Murris J, Borget I, Guilloux A, Martelli N, Katsahian S. Assessment of Performance, Interpretability, and Explainability in Artificial Intelligence–Based Health Technologies: What Healthcare Stakeholders Need to Know. Mayo Clinic Proceedings: Digital Health 2023;1(2):120 View
  3. Alanazi A. Clinicians’ Views on Using Artificial Intelligence in Healthcare: Opportunities, Challenges, and Beyond. Cureus 2023 View
  4. Alanzi T, Alanazi F, Mashhour B, Altalhi R, Alghamdi A, Al Shubbar M, Alamro S, Alshammari M, Almusmili L, Alanazi L, Alzahrani S, Alalouni R, Alanzi N, Alsharifa A. Surveying Hematologists’ Perceptions and Readiness to Embrace Artificial Intelligence in Diagnosis and Treatment Decision-Making. Cureus 2023 View
  5. Shevtsova D, Ahmed A, Boot I, Sanges C, Hudecek M, Jacobs J, Hort S, Vrijhoef H. Trust in and Acceptance of Artificial Intelligence Applications in Medicine: Mixed Methods Study. JMIR Human Factors 2024;11:e47031 View
  6. Viberg Johansson J, Dembrower K, Strand F, Grauman Å. Women’s perceptions and attitudes towards the use of AI in mammography in Sweden: a qualitative interview study. BMJ Open 2024;14(2):e084014 View
  7. Scharre A, Scholler D, Gesell‐May S, Müller T, Zablotski Y, Ertel W, May A. Comparison of veterinarians and a deep learning tool in the diagnosis of equine ophthalmic diseases. Equine Veterinary Journal 2024 View
  8. Swain S, Muduli K. Uncovering the Issues Associated with AI and other Disruptive Technology Enabled Operational Practices in Healthcare Sectors in India. Recent Patents on Engineering 2024;18(5) View
  9. Pringle A, Kumaran V, Missier M, Nadar A. Perceptiveness and Attitude on the use of Artificial Intelligence (AI) in Dentistry among Dentists and Non-Dentists - A Regional Survey. Journal of Pharmacy and Bioallied Sciences 2024;16(Suppl 2):S1481 View
  10. Dingel J, Kleine A, Cecil J, Sigl A, Lermer E, Gaube S. Predictors of Healthcare Practitioners' Intention to Use AI-Enabled Clinical Decision Support Systems (AI-CDSSs): A Meta-Analysis Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Preprint). Journal of Medical Internet Research 2024 View
  11. Rane N, Choudhary S, Rane J. Acceptance of artificial intelligence: key factors, challenges, and implementation strategies. SSRN Electronic Journal 2024 View

Books/Policy Documents

  1. Rao Bhavaraju S. Artificial Intelligence in Medicine and Surgery - An Exploration of Current Trends, Potential Opportunities, and Evolving Threats - Volume 1. View