2024
DOI: 10.1186/s12886-024-03331-x
|View full text |Cite
|
Sign up to set email alerts
|

Study of myopia progression and risk factors in Hubei children aged 7–10 years using machine learning: a longitudinal cohort

Wenping Li,
Yuyang Tu,
Lianhong Zhou
et al.

Abstract: Background To investigate the trend of refractive error among elementary school students in grades 1 to 3 in Hubei Province, analyze the relevant factors affecting myopia progression, and develop a model to predict myopia progression and the risk of developing high myopia in children. Methods Longitudinal study. Using a cluster-stratified sampling method, elementary school students in grades 1 to 3 (15,512 in total) from 17 cities in Hubei Province… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
2

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 33 publications
0
1
0
Order By: Relevance
“…The global prevalence of myopia is undergoing a rapid increase, with projections estimating that by 2050, there will be 4.758 billion myopic individuals worldwide, constituting 49.8% of the total population. 29 In our previous study conducted in 2019, 30 we focused on elementary students (grades 1–3) and utilized machine learning alongside questionnaires to identify high-risk groups for myopia progression whose results inspired us the importance of myopia management in younger students. As we continued our routine work, we uncovered significant regional differences in myopia rates within Hubei.…”
Section: Discussionmentioning
confidence: 99%
“…The global prevalence of myopia is undergoing a rapid increase, with projections estimating that by 2050, there will be 4.758 billion myopic individuals worldwide, constituting 49.8% of the total population. 29 In our previous study conducted in 2019, 30 we focused on elementary students (grades 1–3) and utilized machine learning alongside questionnaires to identify high-risk groups for myopia progression whose results inspired us the importance of myopia management in younger students. As we continued our routine work, we uncovered significant regional differences in myopia rates within Hubei.…”
Section: Discussionmentioning
confidence: 99%