Accurate prediction of myopic progression and high myopia by machine learning.

ABSTRACT:

Background

Myopia is a leading cause of visual impairment in Asia and worldwide. However, accurately predicting the progression of myopia and the high risk of myopia remains a challenge. This study aims to develop a predictive model for the development of myopia.

Methods

We first retrospectively gathered 612 530 medical records from five independent cohorts, encompassing 227 543 patients ranging from infants to young adults. Subsequently, we developed a multivariate linear regression algorithm model to predict the progression of myopia and the risk of high myopia.

Result

The model to predict the progression of myopia achieved an R² value of 0.964 vs a mean absolute error (MAE) of 0.119D [95% confidence interval (CI): 0.119, 1.146] in the internal validation

SUBMITTER: Li J 

PROVIDER: S-EPMC10981449 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature