Prediction of Myopia in Adolescents through Machine Learning Methods

Xu Yang, Guo Chen, Yunchong Qian, Yuhan Wang, Yisong Zhai, Debao Fan and Yang Xu
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Xu Yang: School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Guo Chen: School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Yunchong Qian: School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Yuhan Wang: School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Yisong Zhai: School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Debao Fan: School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Yang Xu: School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China

IJERPH, 2020, vol. 17, issue 2, 1-14

Abstract: According to literature, myopia has become the second most common eye disease in China, and the incidence of myopia is increasing year by year, and showing a trend of younger age. Previous researches have shown that the occurrence of myopia is mainly determined by poor eye habits, including reading and writing posture, eye length, and so on, and parents’ heredity. In order to better prevent myopia in adolescents, this paper studies the influence of related factors on myopia incidence in adolescents based on machine learning method. A feature selection method based on both univariate correlation analysis and multivariate correlation analysis is used to better construct a feature sub-set for model training. A method based on GBRT is provided to help fill in missing items in the original data. The prediction model is built based on SVM model. Data transformation has been used to improve the prediction accuracy. Results show that our method could achieve reasonable performance and accuracy.

Keywords: machine learning; myopia in adolescents; correlation analysis; artificial intelligence (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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