A machine-learning approach to discerning prevalence and causes of myopia among elementary students in Hubei

Tu, Yifeng; Hu, Xuemin; Zeng, Caiqiong; Ye, Meihong; Zhang, Peng; Jin, Xiaoqin; Zhang, Jianwei; Zhou, Lianhong

doi:10.1007/s10792-022-02279-5

Cited by 9 publications

(4 citation statements)

References 26 publications

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“…The most significant mechanism involved in the development of myopia is the elongation of the axial length of the eyeball [ 8 , 9 ]. Among the environmental contributors to myopia, factors such as extensive engagement in near work, limited participation in outdoor activities, and disturbances in circadian rhythm control have been identified [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Ciliary muscles contraction leads to axial length extension——The possible initiating factor for myopia

Meng,

Yang,

Zhou

2024

PLoS ONE

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Purpose This study aimed to investigate the underlying factors driving the onset of myopia, specifically the role of the ciliary muscle’s contraction in the elongation of the axial length of the eye. Methods The retrospective study was conducted utilizing data from three ophthalmic centers in Shanghai and Beijing. Both Chinese and Caucasian children were involved. The axial length of the subjects’ eyes was measured in both relaxed and contracted state of the ciliary muscle. A comprehensive mechanical model was also developed to observe the influence of ciliary muscle contraction on the axial length. Results This study included a sample of 198 right eyes of 198 myopic children. Of these, 97 were male and 101 were female, 126 were of Chinese ethnicity and 72 were Caucasian. The age of onset for myopia ranged from 5.9 to 16.9 years old. The axial length of the eye decreased 0.028 ± 0.007mm following dilation, indicating relaxation of the ciliary muscle (t paired student = 15.16, p = 6.72 x 10−35). In contrast, ciliary muscle contraction resulted in an increase in axial length. Considering proportionality, a significant 90.4% (179 eyes) exhibited a reduced axial length, while a minor 9.6% (19 eyes) demonstrated an increase post-mydriasis. Finite element modeling demonstrated that muscle contraction caused a tension force that transmits towards the posterior pole of the eye, causing it to extend posteriorly. Conclusion The contraction of the ciliary muscle leads to an extension of the axial length. This could potentially be the initiating factor for myopia.

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Section: Introductionmentioning

confidence: 99%

Ciliary muscles contraction leads to axial length extension——The possible initiating factor for myopia

Meng,

Yang,

Zhou

2024

PLoS ONE

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“…Myopia classification model based on machine learning algorithm can well determine the influencing factors of students’ myopia, but the current research is limited to a specific school period. The similarities and differences in the factors affecting myopia among students in each school period need to be explored ( 23 , 24 ). External factors and students’ activity habits vary with age.…”

Section: Introductionmentioning

confidence: 99%

“…Machine learning has been applied to myopia research in recent years. Examples include predicting axial length of eye and identifying factors influencing myopia (21)(22)(23)(24)(25)(26). Myopia classification model based on machine learning algorithm can well determine the influencing factors of students' myopia, but the current research is limited to a specific school period.…”

Section: Introductionmentioning

confidence: 99%

Machine learning to analyze the factors influencing myopia in students of different school periods

Tong

Huang

et al. 2023

Front. Public Health

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PurposeWe aim to develop myopia classification models based on machine learning algorithms for each schooling period, and further analyze the similarities and differences in the factors influencing myopia in each school period based on each model.DesignRetrospective cross-sectional study.ParticipantsWe collected visual acuity, behavioral, environmental, and genetic data from 7,472 students in 21 primary and secondary schools (grades 1–12) in Jiamusi, Heilongjiang Province, using visual acuity screening and questionnaires.MethodsMachine learning algorithms were used to construct myopia classification models for students at the whole schooling period, primary school, junior high school, and senior high school period, and to rank the importance of features in each model.ResultsThe main influencing factors for students differ by school section, The optimal machine learning model for the whole schooling period was Random Forest (AUC = 0.752), with the top three influencing factors being age, myopic grade of the mother, and Whether myopia requires glasses. The optimal model for the primary school period was a Random Forest (AUC = 0.710), with the top three influences being the myopic grade of the mother, age, and extracurricular tutorials weekly. The Junior high school period was an Support Vector Machine (SVM; AUC = 0.672), and the top three influencing factors were gender, extracurricular tutorial subjects weekly, and whether can you do the “three ones” when reading and writing. The senior high school period was an XGboost (AUC = 0.722), and the top three influencing factors were the need for spectacles for myopia, average daily time spent outdoors, and the myopic grade of the mother.ConclusionFactors such as genetics and eye use behavior all play an essential role in students’ myopia, but there are differences between school periods, with those in the lower levels focusing on genetics and those in the higher levels focusing on behavior, but both play an essential role in myopia.

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“…7,8 Among the environmental contributors to myopia, factors such as extensive engagement in near work, limited participation in outdoor activities, and disturbances in circadian rhythm control have been identi ed. 9 Previous investigations into the etiology of myopia have revealed several potential factors and mechanisms contributing to its development. Accommodation, the eye's ability to adjust focus, has been extensively studied in relation to myopia.…”

Section: Introductionmentioning

confidence: 99%

Ciliary muscles contraction leads to axial length extension —— The possible initiating factor for myopia

Zhou,

Wang,

Fan

et al. 2023

Preprint

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This study aimed to investigate the underlying factors driving the onset of myopia, specifically the role of the ciliary muscle’s contraction in the elongation of the axial length of the eye. The retrospective study was conducted utilizing data from three ophthalmic centers in Shanghai and Beijing. Both Chinese and Caucasian children were involved. The axial length of the subjects’ eyes was measured in both relaxed and contracted state of the ciliary muscle. A comprehensive mechanical model was also developed to observe the influence of ciliary muscle contraction on the axial length. This study included a sample of 198 right eyes of 198 myopic children. Of these, 97 were male and 101 were female, 126 were of Chinese ethnicity and 72 were Caucasian. The age of onset for myopia ranged from 5.9 to 16.9 years old. The axial length of the eye decreased 0.028 ± 0.007mm following dilation, indicating relaxation of the ciliary muscle (t paired student = 15.16, p = 6.72 x 10− 35). In contrast, ciliary muscle contraction resulted in an increase in axial length. Considering proportionality, a significant 90.4% (179 eyes) exhibited a reduced axial length, while a minor 9.6% (19 eyes) demonstrated an increase post-mydriasis. Finite element modeling demonstrated that muscle contraction caused a tension force that transmits towards the posterior pole of the eye, causing it to extend posteriorly. The contraction of the ciliary muscle leads to an extension of the axial length. This could potentially be the initiating factor for myopia.

show abstract

A machine-learning approach to discerning prevalence and causes of myopia among elementary students in Hubei

Cited by 9 publications

References 26 publications

Ciliary muscles contraction leads to axial length extension——The possible initiating factor for myopia

Ciliary muscles contraction leads to axial length extension——The possible initiating factor for myopia

Machine learning to analyze the factors influencing myopia in students of different school periods

Ciliary muscles contraction leads to axial length extension —— The possible initiating factor for myopia

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