A Quality Assessment Rubric for Artificial Intelligence–Generated Patient-Friendly Radiology Reports
Although requiring further training and validation, AI rubric application could enable scalable quality assurance and safer clinical integration of AI-generated communications.
Authors
- David B. Larson (ORCID: https://orcid.org/0000-0002-1157-5905)
- Bonnie A. Armstrong (ORCID: https://orcid.org/0000-0002-0513-0424)
- Arogya Koirala (ORCID: https://orcid.org/0009-0007-0304-5350)
- Zhongnan Fang (ORCID: https://orcid.org/0000-0003-3463-7766)
- Hye Sun Na
- Andrew Johnston
- Akshay Chaudhari
- Lina Cheuy
- Donghe Lyu
- Marcello Chang
Institutions
- Palo Alto University (US)
- Artificial Intelligence in Medicine (Canada) (CA)
- Stanford University (US)
Publication Details
- Journal
- American Journal of Roentgenology
- Published
- 2026-09-09
- DOI
- https://doi.org/10.2214/ajr.26.35532
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00