From data-rich to evidence-ready: A narrative review of generative artificial intelligence as a statistical scaffold in medical radiation sciences research.
- DOI
- 10.1016/j.jmir.2026.102447
- Published
- 2026 Jul
- Container
- Journal of medical imaging and radiation sciences
- Publisher
- Not recorded
- Open access
- no
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1016/j.jmir.2026.102447,
title = {From data-rich to evidence-ready: A narrative review of generative artificial intelligence as a statistical scaffold in medical radiation sciences research.},
author = {Currie GM and Hewis J},
year = {2026},
journal = {Journal of medical imaging and radiation sciences},
doi = {10.1016/j.jmir.2026.102447},
url = {https://doi.org/10.1016/j.jmir.2026.102447}
}RIS
TY - JOUR TI - From data-rich to evidence-ready: A narrative review of generative artificial intelligence as a statistical scaffold in medical radiation sciences research. AU - Currie GM AU - Hewis J PY - 2026 JO - Journal of medical imaging and radiation sciences DO - 10.1016/j.jmir.2026.102447 UR - https://doi.org/10.1016/j.jmir.2026.102447 ER -
APA
GM, C., & J, H. (2026). From data-rich to evidence-ready: A narrative review of generative artificial intelligence as a statistical scaffold in medical radiation sciences research.. Journal of medical imaging and radiation sciences. https://doi.org/10.1016/j.jmir.2026.102447
Source records
- pubmed · retrieved 2026-09-26T09:16:57.095Z
- europe-pmc · retrieved 2026-09-26T09:16:57.105Z