Transparent reporting is central to reproducible radiological AI research: A call to action
Strengthening transparent reporting is a prerequisite for reproducible and clinically translatable radiological AI research. Embedding reporting within study design, aligning stakeholder expectations, and improving access to reproducibility-enabling resources are essential to enhance credibility, facilitate independent evaluation, and support safe clinical implementation of AI in radiology.
Authors
- Kaspar L. Yaxley (ORCID: https://orcid.org/0000-0003-2415-8390)
- Minh Chau (ORCID: https://orcid.org/0000-0003-2306-3437)
- Qi Wu (ORCID: https://orcid.org/0000-0002-2114-9037)
- Samuel White
Institutions
- Charles Sturt University (AU)
- Fiona Stanley Hospital (AU)
- Flinders Medical Centre (AU)
- The University of Adelaide (AU)
Publication Details
- Journal
- European Journal of Radiology
- Published
- 2026-03-07
- DOI
- https://doi.org/10.1016/j.ejrad.2026.112777
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00