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Prediction of Myopia in Adolescents through Machine Learning Methods

Author

Listed:
  • 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)

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.

Suggested Citation

  • Xu Yang & Guo Chen & Yunchong Qian & Yuhan Wang & Yisong Zhai & Debao Fan & Yang Xu, 2020. "Prediction of Myopia in Adolescents through Machine Learning Methods," IJERPH, MDPI, vol. 17(2), pages 1-14, January.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:2:p:463-:d:307337
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    Cited by:

    1. Xialv Lin & Xiaofeng Wang & Yuhan Wang & Xuejie Du & Lizhu Jin & Ming Wan & Hui Ge & Xu Yang, 2021. "Optimized Neural Network Based on Genetic Algorithm to Construct Hand-Foot-and-Mouth Disease Prediction and Early-Warning Model," IJERPH, MDPI, vol. 18(6), pages 1-25, March.

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