ArticleBMJ open ophthalmology2023
Prediction of refractive error and its progression: a machine learning-based algorithm.
Article in BMJ open ophthalmology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Development of a deep learning model to predict cycloplegic myopia and pre- myopia: based on a large-scale screening of school-aged children.Eye (London, England) · 2026Article
- 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
- A refractive error prediction model for children and adolescents based on ocular biometric parameters.BMC ophthalmology · 2026Observational
- Refractive Errors and Ocular Biometric Parameters in Children with Autism Spectrum Disorder in Handan: A Cross-Sectional Study.International journal of general medicine · 2026Article
- Prediction of refractive error in adolescents using a multimodal large language model.Frontiers in medicine · 2026Article
- Myopia Prediction Using Machine Learning: An External Validation Study.Vision (Basel, Switzerland) · 2025Article
- IMI-Interventions for Controlling Myopia Onset and Progression 2025.Investigative ophthalmology & visual science · 2025Review
- Artificial intelligence applications in refractive error management: A systematic review and meta-analysis.PLOS digital health · 2025Article
- Improving the estimation of the spherical equivalent subjective refraction using objective information on accommodation.Biomedical optics express · 2025Article
- Application of artificial intelligence in myopia prevention and control.Pediatric investigation · 2025Review
- Refractive development III: Variations in emmetropia and ametropia.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2025Article
- Artificial intelligence in ophthalmology: opportunities, challenges, and ethical considerations.Medical hypothesis, discovery & innovation ophthalmology journal · 2025Review
- Artificial Intelligence in Optometry: Current and Future Perspectives.Clinical optometry · 2025Review
- Cross-population validation of the PreMO risk indicator for predicting myopia onset in children.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2025Article
- Forecasting Myopic Maculopathy Risk Over a Decade: Development and Validation of an Interpretable Machine Learning Algorithm.Investigative ophthalmology & visual science · 2024Article
- Artificial intelligence in the anterior segment of eye diseases.International journal of ophthalmology · 2024Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveMyopia is the refractive error that shows the highest prevalence for younger ages in Southeast Asia and its projection over the next decades indicates that this situation will worsen. Nowadays, several management solutions are being applied to help fight its onset and development, nonetheless, the applications of these techniques depend on a clear and reliable assessment of risk to develop myopia. METHODS AND ANALYSIS: In this study, population-based data of Chinese children were used to develop a machine learning-based algorithm that enables the risk assessment of myopia's onset and development. Cross-sectional data of 12 780 kids together with longitudinal data of 226 kids containing age, gender, biometry and refractive parameters were used for the development of the models.
resultsA combination of support vector regression and Gaussian process regression resulted in the best performing algorithm. The Pearson correlation coefficient between prediction and measured data was 0.77, whereas the bias was -0.05 D and the limits of agreement was 0.85 D (95% CI: -0.91 to 0.80D). DISCUSSION: The developed algorithm uses accessible inputs to provide an estimate of refractive development and may serve as guide for the eye care professional to help determine the individual best strategy for management of myopia.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.