Machine Learning Approaches in High Myopia: Systematic Review and Meta-Analysis.

ABSTRACT:

Background

In recent years, with the rapid development of machine learning (ML), it has gained widespread attention from researchers in clinical practice. ML models appear to demonstrate promising accuracy in the diagnosis of complex diseases, as well as in predicting disease progression and prognosis. Some studies have applied it to ophthalmology, primarily for the diagnosis of pathologic myopia and high myopia-associated glaucoma, as well as for predicting the progression of high myopia. ML-based detection still requires evidence-based validation to prove its accuracy and feasibility.

Objective

This study aims to discern the performance of ML methods in detecting high myopia and pathologic myopia in clinical practice, thereby providing evidence-based support for the future

SUBMITTER: Zuo H 

PROVIDER: S-EPMC11748443 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature