Deep Learning Prediction of Childhood Myopia Progression Using Fundus Image and Refraction Data.

ABSTRACT:

Importance

Childhood myopia is a global health concern with escalating prevalence and can lead to severe irreversible visual impairment. Early prediction of myopia progression is crucial for timely intervention to prevent high myopia and associated complications.

Objective

To develop and validate a quantitative method, based on a deep learning method and using only fundus images and baseline refraction data, to predict both myopia progression trajectory and high myopia risk in schoolchildren.

Design, setting, and participants

This longitudinal school-based cohort study (Anyang Childhood Eye Study) was conducted from February 2012 to May 2018, with annual follow-up examinations from February 2013 to May 2018. Grade 1 students, aged 6 to 9 years, were recruited from 11

SUBMITTER: Kang MT 

PROVIDER: S-EPMC12836131 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature