摘要
该文分析了国内外近视检查数据,统计结果显示中国青少年近视发生率远远超过国际水平,其中8~12岁是近视新增的高发时期,平均每年约有20%的非近视学生转为近视学生,而10~14岁是高度近视新增的危险时期。此外,父母近视情况和户外活动时间对近视形成的影响最大,高于电脑使用时间和看电视时间的影响。该文采用5种集成学习方法对未来视力情况进行预测,综合考虑鲁棒性和精确度,随机森林模型预测效果最好,其中近视的预测准确率在70%训练集、30%测试集划分的情况下为92.8%。
This paper analyzes myopia examination data at home and abroad.Statistics show that the incidence of myopia in Chinese adolescents far exceeds the international adolescents.8 to 12 years old is a period when the number of myopia is increasing rapidly.About 20%of non-myopia students turn into myopia students every year in this period.The age of 10 to 14 is a dangerous period of suffering from high myopia.Time for outdoor activities and parents’myopia have the greatest impact on the occurrence of myopia,higher than that of the time spent on computer and the time spent on watching TV.This paper uses five ensemble learning methods to predict people’s future vision.Considering the robustness and accuracy,the random forest model has the best prediction effect.The prediction accuracy of myopia is 92.8%in the case of 70%training set and 30%test set.
作者
黄峻嘉
张琪
赵娜
李蓉
苏宇涵
周涛
HUANG Jun-jia;ZHANG Qi;ZHAO Na;LI Rong;SU Yu-han;ZHOU Tao(National Pilot School of Software,Yunnan University,Kunming,650504;EYE SEE Ophthalmology Clinic,Eye See Inc,Chengdu,610041;Big Data Research Center,University of Electronic Science and Technology of China,Chengdu,611731)
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2021年第2期256-260,共5页
Journal of University of Electronic Science and Technology of China
基金
国家重点研发计划(2018YFB2100100)
国家自然科学基金(62066048,11975071)
中国博士后科学基金(2020M673312)。
关键词
集成学习
近视
预测
随机森林
ensemble learning
myopia
prediction
random forest
