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

New Resources for Medical Education (213) e-Learning and Digital Medical Education (1629) New Methods and Approaches in Medical Education (665) Artificial Intelligence (4933) Artificial Intelligence (AI) in Medical Education (828)

Published on in Vol 12 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/91626, first published .
Four domains of Health CARE-AI principles: Values, Competence, Accountability, Structural Equity.

Principles for Responsible AI in Health Professions Education, Research, and Care: Health CARE-AI (Contextual, Accountable, Responsible, and Equitable Artificial Intelligence) Framework Delphi Consensus Study

Principles for Responsible AI in Health Professions Education, Research, and Care: Health CARE-AI (Contextual, Accountable, Responsible, and Equitable Artificial Intelligence) Framework Delphi Consensus Study

Authors of this article:

Lyn K Sonnenberg1, 2 Author Orcid Image ;   David Wiljer1, 3, 4 Author Orcid Image ;   Muhammad Mamdani5, 6 Author Orcid Image ;   Victor Do1, 2 Author Orcid Image ;   Brandon Tang1, 7 Author Orcid Image ;   Babar Haroon8 Author Orcid Image ;   Bizav Jaffer1, 9 Author Orcid Image ;   Jerry Maniate1, 9 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Mahgoub A, Singh A, Mahgoub A. Governing Generative Artificial Intelligence in Anatomy Education: A Proposed Risk-Tiered Framework for Donor-Derived Material, Anatomical Fidelity, and Assessment. Cureus 2026 View
  2. Simoni J, Pereira J, Crespo Sánchez S, Egaña-Yin D, García-Gargallo C, Hertog O, Idoate A, López-Ortiz L, Morales-Gutiérrez I, Romero A, Santiago-Martínez P, Sawczyn G, Vahamaki A, Urtubia-Fernandez J, Mengual E. What and when: a Delphi study identifying AI competencies and learning objectives for medical students. Frontiers in Digital Health 2026;8 View