Screening for novel risk factors related to high myopia using machine learning.

ABSTRACT:

Background

High myopia-related complications have become a major cause of irreversible vision loss. Evaluating the association between potential factors and high myopia can provide insights into pathophysiologic mechanisms and further intervention targets for myopia progression.

Method

Participants aged 12-25 years from National Health and Nutrition Examination Survey 2001-2006 were selected for the analysis. Myopia was defined as spherical equivalent (sum of spherical error and half of the cylindrical error) of any eyes ≤-0.5 diopters. High myopia was defined as the spherical equivalent of any eye ≤ - 5.00 diopters. Essential variables were selected by Random Forest algorithm and verified by multivariable logistic regression.

Results

A total of 7,033 participants and

SUBMITTER: Zhang R 

PROVIDER: S-EPMC9558412 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature