AI-assisted automated interpretation of corneal topography in orthokeratology patients: enhancing diagnostic precision and efficiency

20250 citationsJournal Articlegold Open Access

Authors

Daohuan Kang · Children's Hospital of Zhejiang University

Jia Feng · Children's Hospital of Zhejiang University

Jiao Zhan · Children's Hospital of Zhejiang University

A. Grzybowski · Children's Hospital of Zhejiang University

Wen Sun · Children's Hospital of Zhejiang University

Kai Jin · Children's Hospital of Zhejiang University

Abstract

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.

Topics & Keywords

Ophthalmology and Visual Impairment Studies Corneal surgery and disorders Retinopathy of Prematurity Studies

Publication Details

Published in: International Journal of Ophthalmology

Volume 18, Issue 12, pp. 2217-2224

DOI: 10.18240/ijo.2025.12.01

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AI-assisted automated interpretation of corneal topography in orthokeratology patients: enhancing diagnostic precision and efficiency

Authors

Abstract

Topics & Keywords

Publication Details