| Literature DB >> 34645966 |
Xiaotong Han1, Chi Liu1,2, Yanxian Chen1,3, Mingguang He4.
Abstract
Myopia is a leading cause of visual impairment and has raised significant international concern in recent decades with rapidly increasing prevalence and incidence worldwide. Accurate prediction of future myopia risk could help identify high-risk children for early targeted intervention to delay myopia onset or slow myopia progression. Researchers have built and assessed various myopia prediction models based on different datasets, including baseline refraction or biometric data, lifestyle data, genetic data, and data integration. Here, we summarize all related work published in the past 30 years and provide a comprehensive review of myopia prediction methods, datasets, and performance, which could serve as a useful reference and valuable guideline for future research.Entities:
Mesh:
Year: 2021 PMID: 34645966 PMCID: PMC9046389 DOI: 10.1038/s41433-021-01805-6
Source DB: PubMed Journal: Eye (Lond) ISSN: 0950-222X Impact factor: 4.456