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A Novel Time-Aware Deep Learning Model Predicting Myopia in Children and Adolescents | Synapse

June 13, 2024Open Access

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A Novel Time-Aware Deep Learning Model Predicting Myopia in Children and Adolescents

AVAna Maria VarošanecUniversity Hospital Centre Zagreb LMLeon MarkovićMinistry of Health ZSZdenko SonickiAndrija Stampar Teaching Institute of Public Health

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Resumen

To quantitatively predict children's and adolescents' spherical equivalent (SE) by leveraging their variable-length historical vision records.

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Cite This Study

Varošanec et al. (Thu,) studied this question.

synapsesocial.com/papers/68e64d81b6db6435875de7c6 https://doi.org/https://doi.org/10.1016/j.xops.2024.100563

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Machine Learning in Medicine2015 · 3,462 citations
2Annual Myopia Progression and Subsequent 2-Year Myopia Progression in Singaporean Children2020 · 38 citations
3Risk Factors for Incident Myopia in Australian Schoolchildren2013 · 338 citations
4Machine Learning for Prediction in Electronic Health Data2018 · 98 citations
5Childhood gene-environment interactions and age-dependent effects of genetic variants associated with refractive error and myopia: The CREAM Consortium2016 · 109 citations