Machine Learning Models for Predicting Cycloplegic Refractive Error and Myopia Status Based on Non-Cycloplegic Data in Chinese Students-Reference-Cited by-同舟云学术

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Machine Learning Models for Predicting Cycloplegic Refractive Error and Myopia Status Based on Non-Cycloplegic Data in Chinese Students

Published:2024-08-09 Issue:8 Volume:13 Page:16
ISSN:2164-2591
Container-title:Translational Vision Science & Technology
language:en
Short-container-title:Trans. Vis. Sci. Tech.

Author:

Ying Bole¹,Chandra Rajat S.²,Wang Jianyong³,Cui Hongguang³,Oatts Julius T.⁴

Affiliation:

1. Lower Merion High School, Ardmore, PA, USA

2. University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA

3. Department of Ophthalmology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, P. R. China

4. Department of Ophthalmology, University of California San Francisco, San Francisco, CA, USA

Publisher

Association for Research in Vision and Ophthalmology (ARVO)

Reference35 articles.

1. IMI impact of myopia;Sankaridurg;Invest Ophthalmol Vis Sci,2021

2. IMI risk factors for myopia;Morgan;Invest Ophthalmol Vis Sci,2021

3. Complications of pathologic myopia;Cho;Eye Contact Lens,2016

4. IMI—defining and classifying myopia: a proposed set of standards for clinical and epidemiologic studies;Flitcroft;Invest Ophthalmol Vis Sci,2019

5. Correlation of structural and electrophysiological changes in the retina of young high myopes;Koh;Ophthalmic Physiol Opt,2014

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