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

Journals

  1. Khan N, Nwafor Okoli C, Ekpin V, Attai K, Chukwudi N, Sabi H, Akwaowo C, Osuji J, Benavente L, Uzoka F. Adoption and utilization of medical decision support systems in the diagnosis of febrile Diseases: A systematic literature review. Expert Systems with Applications 2023;220:119638 View
  2. Gould D, Dowsey M, Spelman T, Bailey J, Bunzli S, Rele S, Choong P. Established and Novel Risk Factors for 30-Day Readmission Following Total Knee Arthroplasty: A Modified Delphi and Focus Group Study to Identify Clinically Important Predictors. Journal of Clinical Medicine 2023;12(3):747 View
  3. Fröhlich P, Mirnig A, Falcioni D, Schrammel J, Diamond L, Fischer I, Tscheligi M. Effects of reliability indicators on usage, acceptance and preference of predictive process management decision support systems. Quality and User Experience 2022;7(1) View