基于多元线性回归的空腹血糖影响因素分析方法

计算机科学 ›› 2018, Vol. 45 ›› Issue (11A): 545-547.

基于多元线性回归的空腹血糖影响因素分析方法

张福旺, 苑会娟

哈尔滨理工大学测控技术与通信工程学院哈尔滨150080

出版日期:2019-02-26 发布日期:2019-02-26
通讯作者: 张福旺(1990-),男,硕士生,主要研究方向为计算机视觉、自然语言处理、数理统计,E-mail:3537064032@qq.com
作者简介:苑会娟(1963-),女,教授,硕士生导师,主要研究方向为传感技术、3D测量技术,E-mail:huijuany@126.com。

Analysis of Factors Influencing Fasting Plasma Glucose Based on Multiple Linear Regression

ZHANG Fu-wang, YUAN Hui-juan

Institute of Measurement and Control Technology and Communication Engineering,Harbin University of Science and Technology,Harbin 150080,China

Online:2019-02-26 Published:2019-02-26

摘要/Abstract

摘要： 通过分析空腹血糖影响因素的关系,提出了一种基于多元线性回归分析的空腹血糖影响因素分析方法。首先,收集影响空腹血糖的主要因素数据,包括血清总胆固醇、甘油三酯、空腹胰岛素、糖化血红蛋白;然后,通过散点图对这些影响因素进行分析和确定,利用收集到的数据构建基于最小二乘法的多元线性回归模型,并通过逐步回归分析得到修正后的模型;最后,运用此模型确定了影响空腹血糖的关键因素,以为糖尿病患者的平时饮食给予指导以及为医生的临床治疗提供参考。

关键词: 多元线性回归, 空腹血糖, 逐步回归, 最小二乘法

Abstract: A kind of fasting plasma glucose factors analysis method based on multiple linear regression analysis was proposed by analyzing the relationship ofinfluencing factors of fasting plasma glucose.Firstly,the data of major factors influencing fasting plasma glucose is collected,including serum total cholesterol,triglyceride,fasting insulin,and glyca-ted hemoglobin.Later,these influencing factors are analyzed and determined through scatter diagram.The multiple li-near regression model based on least square method is constructed by the collected data.Meanwhile,through stepwise regression,the revised model is otained.At last,this model is applied to determine the key factors that affect fasting pla-sma glucose,so as to give diet guidance for diabetic patients,and provide reference for the clinical treatment of doctors.

Key words: Fasting plasma glucose, Least-square method, Multiple linear regression, Stepwise regression

中图分类号:

O212.4

张福旺, 苑会娟. 基于多元线性回归的空腹血糖影响因素分析方法[J]. 计算机科学, 2018, 45(11A): 545-547. https://doi.org/

ZHANG Fu-wang, YUAN Hui-juan. Analysis of Factors Influencing Fasting Plasma Glucose Based on Multiple Linear Regression[J]. Computer Science, 2018, 45(11A): 545-547. https://doi.org/

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