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

Digital Health Reviews (1724) Machine Learning (2076) Decision Support for Health Professionals (1539) Artificial Intelligence (2129) Applications of AI (287) Health Professionals' Training in eHealth, Digital Medicine, Medical Informatics (186)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73374, first published .
Improving Explainability and Integrability of Medical AI to Promote Health Care Professional Acceptance and Use: Mixed Systematic Review

Improving Explainability and Integrability of Medical AI to Promote Health Care Professional Acceptance and Use: Mixed Systematic Review

Improving Explainability and Integrability of Medical AI to Promote Health Care Professional Acceptance and Use: Mixed Systematic Review

Authors of this article:

Yushu Liu1, 2 Author Orcid Image ;   Chenxi Liu1, 2 Author Orcid Image ;   Jianing Zheng1, 2 Author Orcid Image ;   Chang Xu3 Author Orcid Image ;   Dan Wang4, 5, 6 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

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  2. Majumdar P. Navigating the Speed-Quality Trade-off in AI-Driven Decision-Making. American Journal of Information Science and Technology 2025;9(3):225 View
  3. Eskandar K. Artificial intelligence in hepatology: A comprehensive scoping review of clinical applications, challenges, and future directions. iLIVER 2025;4(4):100205 View
  4. de Souza Jr. F, Aliaga Jr. J, Duarte Jr. P, Crispilho S, Delfino C, Brandão D, Zamprogno e Silva F. From Semantic Modeling to Precision Radiotherapy: An AI Framework Linking Radiobiology, Oncology, and Public Health Integration. Biomedicines 2025;13(12):2862 View