ArticleEye and vision (London, England)2020
A machine learning-based algorithm used to estimate the physiological elongation of ocular axial length in myopic children.
Article in Eye and vision (London, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed.
- Trend of Myopia Incidence Among Adolescents (2018-2025) in Senior High School: An 8-Year Retrospective Study in Multi-Regions of China, With Projections to 2030.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026Article
- 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
- Influence of Cycloplegia on Axial Length Prediction Models in a Paediatric Sample.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026Article
- A refractive error prediction model for children and adolescents based on ocular biometric parameters.BMC ophthalmology · 2026Observational
- Prevalence and associated factors of myopia and axial length-related visual impairment in children and adolescents aged 4-18 years.Scientific reports · 2025Article
- Axial elongation as a marker to identify obvious myopic shift in non-myopic eyes of Chinese children.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2025Article
- Predicting onset of myopic refractive error in children using machine learning on routine pediatric eye examinations only.Scientific reports · 2025Article
- School-level prediction and management of myopia in children and adolescents.Journal of translational medicine · 2025Article
- IMI-Instrumentation for Myopia Management.Investigative ophthalmology & visual science · 2025Review
- Application of artificial intelligence in myopia prevention and control.Pediatric investigation · 2025Review
- Optimizing myopia prediction in children and adolescents using machine learning: a multi-factorial risk assessment model.Frontiers in medicine · 2025Article
- Prediction of myopia onset and shift in premyopic school-aged children: a machine learning-based algorithm.Frontiers in medicine · 2025Article
- Physiological growth of ocular axial length among Chinese children and teenagers: A 6-year cohort study.PloS one · 2025Article
- Article
- Forecasting Myopic Maculopathy Risk Over a Decade: Development and Validation of an Interpretable Machine Learning Algorithm.Investigative ophthalmology & visual science · 2024Article
- Development and validation of predictive models for myopia onset and progression using extensive 15-year refractive data in children and adolescents.Journal of translational medicine · 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
- Insights into artificial intelligence in myopia management: from a data perspective.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024Review
- Panretinal Optical Coherence Tomography.IEEE transactions on medical imaging · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAxial myopia is the most common type of myopia. However, due to the high incidence of myopia in Chinese children, few studies estimating the physiological elongation of the ocular axial length (AL), which does not cause myopia progression and differs from the non-physiological elongation of AL, have been conducted. The purpose of our study was to construct a machine learning (ML)-based model for estimating the physiological elongation of AL in a sample of Chinese school-aged myopic children.
methodsIn total, 1011 myopic children aged 6 to 18 years participated in this study. Cross-sectional datasets were used to optimize the ML algorithms. The input variables included age, sex, central corneal thickness (CCT), spherical equivalent refractive error (SER), mean K reading (K-mean), and white-to-white corneal diameter (WTW). The output variable was AL. A 5-fold cross-validation scheme was used to randomly divide all data into 5 groups, including 4 groups used as training data and one group used as validation data. Six types of ML algorithms were implemented in our models. The best-performing algorithm was applied to predict AL, and estimates of the physiological elongation of AL were obtained as the partial derivatives of
resultsAmong the six algorithms, the robust linear regression model was the best model for predicting AL, with a
conclusionsThe physiological elongation of the AL is rarely recorded in clinical data in China. In cases of unavailable clinical data, an ML algorithm could provide practitioners a reasonable model that can be used to estimate the physiological elongation of AL, which is especially useful when monitoring myopia progression in orthokeratology lens wearers.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.