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

Ethics, Privacy, and Legal Issues (787) Design and Usability of Clinical Software and EHRs (446) Artificial Intelligence (4528) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (150) Ethical, Legal, and Social Issues in AI (197)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/79863, first published .
Puzzle graphic illustrating AI development lifecycle: data, model, deployment, and feedback loops.

The Ethics of Leveraging Routinely Collected Patient Data for AI Development: Mixed Methods Study

The Ethics of Leveraging Routinely Collected Patient Data for AI Development: Mixed Methods Study

Authors of this article:

Menno T Maris1, 2 Author Orcid Image ;   Joanna E Klopotowska2, 3 Author Orcid Image ;   Ronald Cornet2, 3 Author Orcid Image ;   Mariëtte A Van den Hoven2, 4 Author Orcid Image ;   Joris E Lieverse2, 3 Author Orcid Image ;   Daniel Fernández-Llaneza2, 3 Author Orcid Image ;   Marieke A R Bak1, 2, 5 Author Orcid Image ;   LEAPfROG Consortium6
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Rozenblit L, Labkoff S, Safran C. From Data Stewardship to Model Stewardship: Extending Governance Frameworks for AI Era Health Data Use. Journal of Medical Internet Research 2026;28:e97859 View
  2. Yin X, Song H, Moreira J, Song C, Sun Y. Exploring perceptions of data risks in AI-enabled nursing research: A qualitative study. DIGITAL HEALTH 2026;12 View