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中国科学院大学学报 ›› 2015, Vol. 32 ›› Issue (6): 728-734.DOI: 10.7523/j.issn.2095-6134.2015.06.002

• 数学 • 上一篇    下一篇

现代变量选择方法在青少年近视研究中的应用

海豹1, 李仕明2, 刘洛如3, 申立勇1, 张三国1, 李偲圆2, 李翯3, 康梦田2, 孙芸芸2, 孟博2, 张庆昭1   

  1. 1. 中国科学院大学数学科学学院, 北京 101408;
    2. 首都医科大学附属北京同仁医院眼科中心, 北京 100730;
    3. 河南安阳市眼科医院, 河南 安阳 455000
  • 收稿日期:2014-09-25 修回日期:2015-03-16 发布日期:2015-11-15
  • 通讯作者: 张三国
  • 基金资助:

    国家973重点基础研究发展计划项目(2011CB504601)资助

Juvenile myopia study using modern variable selection methods

HAI Bao1, LI Shiming2, LIU Luoru3, SHEN Liyong1, ZHANG Sanguo1, LI Siyuan2, LI He3, KANG Mengtian2, SUN Yunyun2, MENG Bo2, ZHANG Qingzhao1   

  1. 1. School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 101408, China;
    2. Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China;
    3. Anyang Eye Hospital, Anyang 455000, Henan, China
  • Received:2014-09-25 Revised:2015-03-16 Published:2015-11-15

摘要:

通过分析一组医学数据挖掘出影响青少年近视的关键因素,建立青少年近视患病概率预测模型.数据集主要由两部分组成:一是青少年眼睛的医学测量数据,二是由生活学习习惯调查问卷得到的数据.采用几种现代统计学方法,并利用ROC曲线得到较优的患病概率模型.结果表明,性别、眼轴长度、角膜曲率、工作日睡眠时间、不戴眼镜远视力、远距离调节反应等因素对青少年近视有重要的影响作用,并由此建立预测模型.

关键词: 变量选择, logistic回归, Lasso, MCP, ROC曲线

Abstract:

In this work we used some variable-selection techniques to find out the relevant factors that cause adolescent myopia, and established probabilistic models for myopia prediction. The research is based on a medical dataset consisting of two parts: medical measurement data of the youths and data on daily living habits obtained by questionnaire survey. We used some modern variable selection methods and the ROC curve to evaluate different modes. The results show that gender, axial length, corneal curvature, weekday sleeping time, distance vision without glasses, and remote adjustment reaction have important influences on adolescent myopia.

Key words: variable selection, classical logistic regression, Lasso, MCP, ROC curve

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