AI-assisted automated interpretation of corneal topography in orthokeratology patients: enhancing diagnostic precision and efficiency
AI provides efficient routine corneal topography assessments, while complex cases benefit most from a Human+AI approach, particularly in scenarios requiring nuanced clinical interpretation. The model currently functions as an assistive tool.
Authors
- Jia Feng (ORCID: https://orcid.org/0000-0003-1168-0518)
- Kai Jin (ORCID: https://orcid.org/0000-0003-4369-2417)
- Daohuan Kang
- A. Grzybowski (ORCID: https://orcid.org/0000-0002-5258-6926)
- Jiao Zhan (ORCID: https://orcid.org/0009-0003-8519-2207)
- Wen Sun (ORCID: https://orcid.org/0009-0005-3897-8922)
Institutions
- Children's Hospital of Zhejiang University (CN)
- Foundation for Cardiac Surgery (BE)
- Second Affiliated Hospital of Zhejiang University (CN)
Publication Details
- Journal
- International Journal of Ophthalmology
- Published
- 2025-11-17
- DOI
- https://doi.org/10.18240/ijo.2025.12.01
- Primary Topic
- Ophthalmology and Visual Impairment Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00