The long and short of it: a comprehensive assessment of axial length estimation in myopic eyes from ocular and demographic variables.

ABSTRACT:

Background/objectives

Axial length, a key measurement in myopia management, is not accessible in many settings. We aimed to develop and assess machine learning models to estimate the axial length of young myopic eyes.

Subjects/methods

Linear regression, symbolic regression, gradient boosting and multilayer perceptron models were developed using age, sex, cycloplegic spherical equivalent refraction (SER) and corneal curvature. Training data were from 8135 (28% myopic) children and adolescents from Ireland, Northern Ireland and China. Model performance was tested on an additional 300 myopic individuals using traditional metrics alongside the estimated axial length vs age relationship. Linear regression and receiver operator characteristics (ROC) curves were used for statistica

SUBMITTER: Lingham G 

PROVIDER: S-EPMC11076636 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature