A machine learning-based algorithm used to estimate the physiological elongation of ocular axial length in myopic childr
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RESEARCH
Open Access
A machine learning-based algorithm used to estimate the physiological elongation of ocular axial length in myopic children Tao Tang1,2,3,4†, Zekuan Yu5,6†, Qiong Xu1,2,3,4, Zisu Peng1,2,3,4, Yuzhuo Fan1,2,3,4, Kai Wang1,2,3,4* , Qiushi Ren6, Jia Qu2,7 and Mingwei Zhao1,2,3,4
Abstract Background: Axial 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. Methods: In 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 ALpredicted-age curves based on an unchanged SER value with increasing age. Results: Among the six algorithms, the robust linear regression model was the best model for predicting AL, with a R2 value of 0.87 and relatively minimal averaged errors between the predicted AL and true AL. Based on the partial derivatives of the ALpredicted-age curves, the estimated physiological AL elongation varied from 0.010 to 0.116 mm/ year in male subjects and 0.003 to 0.110 mm/year in female subjects and was influenced by age, SER and K-mean. According to the model, the physiological elongation of AL linearly decreased with increasing age and was negatively correlated with the SER and the K-mean. (Continued on next page)
* Correspondence: [email protected] † Tao Tang and Zekuan Yu contributed equally to this work. 1 Department of Ophthalmology & Clinical Centre of Optometry, Peking University People’s Hospital, Beijing 100044, China 2 College of Optometry, Peking University Health Science Center, Beijing, China Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in t
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