ArticleInternational ophthalmology2022
A machine-learning approach to discerning prevalence and causes of myopia among elementary students in Hubei.
Article in International ophthalmology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 17 citations in OpenAlex.
- The application of artificial intelligence in myopia prediction for children and adolescents: a review.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Review
- Artificial intelligence in pediatric myopia - a narrative review.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Review
- Application of artificial intelligence in myopia prevention and control.Pediatric investigation · 2025Review
- The prevalence of myopia and eye health behaviors among 3 to 18 years: a cross-sectional survey study.BMC public health · 2025Article
- Optimizing myopia prediction in children and adolescents using machine learning: a multi-factorial risk assessment model.Frontiers in medicine · 2025Article
- Community-engaged artificial intelligence research: A scoping review.PLOS digital health · 2024Article
- Bibliometric analysis of hotspots and trends of global myopia research.International journal of ophthalmology · 2024Article
- Machine-learning models to predict myopia in children and adolescents.Frontiers in medicine · 2024Article
- Ciliary muscles contraction leads to axial length extension--The possible initiating factor for myopia.PloS one · 2024Article
- Machine learning to analyze the factors influencing myopia in students of different school periods.Frontiers in public health · 2023Article
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
Abstract
objectiveOur aim is to establish a machine-learning model that will enable us to investigate the key factors influencing the prevalence of myopia in students.
methodsWe performed a cross-sectional study that included 16,653 students from grades 1-3 across 17 cities in Hubei Province. We used questionnaires to discern levels of participation in potential factors contributing to the development of myopia. The relative importance of potential contributors was ranked using machine-learning methods. The students' visual acuity (VA) was measured and those with logMAR VA of > 0.0 underwent a autorefraction test to determine students' refraction status.
resultsThe prevalence of myopia in grades 1, 2, and 3 was 14.70%, 20.54% and 28.93%, respectively. Myopia rates among primary school students in provincial capital city (32.35%) were higher than those in other urban (23.03%) and rural (14.82%) areas. Children with non-myopic parents, only one myopic parent, or both parents having myopia exhibited myopic rates of 16.36%, 25.18%, and 41.37%, respectively. Myopia prevalence was higher in the students who continued to use their eyes at close range for a long time and lower in those engaged longer in outdoor activities. The machine-learning model determined that the top three contributing factors were the students' age (0.36), followed by place of residence (0.34), starting age of education (0.21).
conclusionThe overall prevalence of myopia was 21.52%. Children's age and place of residence were the important influencing factors, but genetics and environmental were also played key roles in myopia development.
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