Malpractice in the machine age: Legal and ethical responses to machine learning in medical imaging
Clinical protocols should specify approved use cases, oversight expectations, documentation of AI involvement, and management of clinician-algorithm disagreement. Training should support critical review of outputs to mitigate automation bias.
Authors
- K.M. Spuur
- M.T. Chau
- A. Pyper
- M. Crossman
- S R White
Institutions
- New South Wales Department of Health (AU)
- Charles Sturt University (AU)
- Queen Elizabeth Hospital (AU)
- The University of Adelaide (AU)
Publication Details
- Journal
- Radiography
- Published
- 2026-02-06
- DOI
- https://doi.org/10.1016/j.radi.2026.103339
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 35.40