ArticleFrontiers in cell and developmental biology2025
Machine learning-driven prediction of cycloplegic refractive error in Chinese children.
Article in Frontiers in cell and developmental biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Machine Learning-Based Prediction of Cycloplegic Refraction Using the Eyerobo Vision Screener: Design-A Cross-Sectional Comparative Device Study.Ophthalmology and therapy · 2026Article
- Myopia Prediction Using Machine Learning: An External Validation Study.Vision (Basel, Switzerland) · 2025Article
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11 authors.
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Abstract
Objective: To develop and validate machine learning (ML) models for predicting cycloplegic spherical equivalent refraction (SER) using non-cycloplegic parameters, addressing challenges in pediatric ophthalmic assessments. Methods: A prospective cohort of 2,274 Chinese children (4,548 eyes) aged 3∼16 years was stratified into development ( Results: In the validation dataset, ML models predicted cycloplegic SER with high Conclusion: ML models provide accurate estimates of cycloplegic SER using non-cycloplegic parameters, offering a practical alternative for pediatric refractive assessments when cycloplegia is infeasible.
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