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

Development and Evaluation of Research Methods, Instruments and Tools (632) Clinical Information and Decision Making (1647) Knowledge Translation and Implementation Science (442) Machine Learning (1730) Clinical Informatics (1160) Digital Health, Telehealth and e-Innovation in Clinical Settings (474) Artificial Intelligence (1723)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50475, first published .
Integrating Explainable Machine Learning in Clinical Decision Support Systems: Study Involving a Modified Design Thinking Approach

Integrating Explainable Machine Learning in Clinical Decision Support Systems: Study Involving a Modified Design Thinking Approach

Integrating Explainable Machine Learning in Clinical Decision Support Systems: Study Involving a Modified Design Thinking Approach

Authors of this article:

Michael Shulha1, 2 Author Orcid Image ;   Jordan Hovdebo3 Author Orcid Image ;   Vinita D’Souza1, 2 Author Orcid Image ;   Francis Thibault4 Author Orcid Image ;   Rola Harmouche4 Author Orcid Image
Article Authors Cited by (4) Tweetations (2) Metrics

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  2. Guleria S, Guptill J, Kumar I, McClintic M, Rojas J. Artificial intelligence integration in healthcare: perspectives and trends in a survey of U.S. health system leaders. BMC Digital Health 2024;2(1) View
  3. Zheng R, Jiang X, Shen L, He T, Ji M, Li X, Yu G. Investigating Clinicians’ Intentions and Influencing Factors for Using an Intelligence-Enabled Diagnostic Clinical Decision Support System in Health Care Systems: Cross-Sectional Survey. Journal of Medical Internet Research 2025;27:e62732 View
  4. Huang X, Ren S, Mao X, Chen S, Chen E, He Y, Jiang Y. Association Between Risk Factors and Major Cancers: Explainable Machine Learning Approach. JMIR Cancer 2025;11:e62833 View