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

Safety and Error Prevention in Health (217) Clinical Information and Decision Making (1553) Artificial Intelligence (1608) Decision Support for Health Professionals (1291) Artificial Intelligence (114)

Published on in Vol 9, No 4 (2022): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38411, first published .
Clinicians’ Perceptions of an Artificial Intelligence–Based Blood Utilization Calculator: Qualitative Exploratory Study

Clinicians’ Perceptions of an Artificial Intelligence–Based Blood Utilization Calculator: Qualitative Exploratory Study

Clinicians’ Perceptions of an Artificial Intelligence–Based Blood Utilization Calculator: Qualitative Exploratory Study

Authors of this article:

Avishek Choudhury1 Author Orcid Image ;   Onur Asan2 Author Orcid Image ;   Joshua E Medow3 Author Orcid Image
Article Authors Cited by (10) Tweetations (5) Metrics

Journals

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  2. Labarta J, Dimitri P, Keiser M, Koledova E, Rivera-Romero O. Evaluating the Usefulness and Ease of Use of a Next-Generation–Connected Drug Delivery Device for Growth Hormone Therapy: Qualitative Study of Health Care Professionals’ Perceptions. JMIR Human Factors 2023;10:e46893 View
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  4. Wosny M, Strasser L, Hastings J. Experience of Health Care Professionals Using Digital Tools in the Hospital: Qualitative Systematic Review. JMIR Human Factors 2023;10:e50357 View
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  6. Bach T, Kristiansen J, Babic A, Jacovi A. Unpacking Human-AI Interaction in Safety-Critical Industries: A Systematic Literature Review. IEEE Access 2024;12:106385 View
  7. Al‐Riyami A, Gammon R, Seheult J, Arora S, Goel R. Artificial intelligence and transfusion education, research and practice: The view from the ISBT Clinical Transfusion Working Party. Vox Sanguinis 2025 View
  8. Tun H, Rahman H, Naing L, Malik O. Trust in AI-Based Clinical Decision Support Systems Among Healthcare Workers: A Systematic Review (Preprint). Journal of Medical Internet Research 2024 View
  9. An S, Teo K, McConnell M, Marshall J, Galloway C, Squirrell D. AI explainability in oculomics: how it works, its role in establishing trust, and what still needs to be addressed. Progress in Retinal and Eye Research 2025:101352 View