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

Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (1010) E-Health Policy and Health Systems Innovation (352) Clinical Information and Decision Making (2007) Decision Support for Health Professionals (1594) New Technologies (114) Adoption and Change Management of eHealth Systems (928) Artificial Intelligence (2252)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/62768, first published .
The Willingness of Doctors to Adopt Artificial Intelligence–Driven Clinical Decision Support Systems at Different Hospitals in China: Fuzzy Set Qualitative Comparative Analysis of Survey Data

The Willingness of Doctors to Adopt Artificial Intelligence–Driven Clinical Decision Support Systems at Different Hospitals in China: Fuzzy Set Qualitative Comparative Analysis of Survey Data

The Willingness of Doctors to Adopt Artificial Intelligence–Driven Clinical Decision Support Systems at Different Hospitals in China: Fuzzy Set Qualitative Comparative Analysis of Survey Data

Authors of this article:

Zhongguang Yu1, 2 Author Orcid Image ;   Ning Hu3 Author Orcid Image ;   Qiuyi Zhao4 Author Orcid Image ;   Xiang Hu5 Author Orcid Image ;   Cunbo Jia6 Author Orcid Image ;   Chunyu Zhang7 Author Orcid Image ;   Bing Liu6 Author Orcid Image ;   Yanping Li1 Author Orcid Image
Article Authors Cited by (8) Tweetations (1) Metrics

Journals

  1. Mohseni Ahangar R, Nouri S, Navari S, Mohammadi Kiani B, Poursiahbidi P. Attitudes of Healthcare Professionals Toward Artificial Intelligence in Clinical Decision-Making: A Cross-Sectional Survey in Iran. InfoScience Trends 2025;2(3):25 View
  2. Velasco L, Wang W. Theoretical appraisal of explanatory paradigms for artificial intelligence usage by medical doctors. DIGITAL HEALTH 2025;11 View
  3. Khalid Al-Kahtani N, Subbarayalu A, Raman V, Jamjoom M, Faiz Saleem Al-Ansary N, Alakrawi Z, Jawad AL-Ibrahim R, Al-Zaki W. Healthcare professionals' and students' perspectives on artificial intelligence in clinical documentation in eastern Saudi Arabia: Factors influencing adoption and utilization. Informatics in Medicine Unlocked 2025;59:101710 View
  4. Islam M, Hosen A, Rony M, Vanu N, Bhuiyan M, Tasnim A, Tiwari A, Yeasmin S, Manik M, Wesley H. Advancing Public Health Surveillance With Artificial Intelligence: A Systematic Review of Real‐Time Data Analytics and Disease Prediction. Advances in Public Health 2025;2025(1) View
  5. Zhou X, Jomhari N, Farid N, Xing Y. Physicians’ perceptions and attitudes on artificial intelligence in hospital management: a qualitative study. BMC Health Services Research 2025;26(1) View
  6. Zou J, Luo G, Li Y. The actual experiences of nurses’ in implementing hypothermia prevention practices during post-anesthesia care unit: a qualitative study based on the PRECEDE-PROCEED model. Frontiers in Medicine 2025;16 View
  7. Kamau D, Mbugua S, Omondi P, Kamau G, Mbugua G, Ngugi R, Ngure J, Ngaruiya N, Wamaitha N, Munene J, Maina N, Gitaka J. Feasibility, acceptance, and workflow integration of an AI-enabled clinical decision support system for non-communicable diseases in Kiambu County, Kenya: A mixed-methods implementation evaluation. Open Research Africa 2026;9:6 View

Books/Policy Documents

  1. Hering M, Zabel S, Neef N, Otto S. HCI International 2025 Posters. View