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 数据分析与知识发现  2019, Vol. 3 Issue (4): 80-89    DOI: 10.11925/infotech.2096-3467.2018.0631
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1吉林大学公共卫生学院 长春 130021
2吉林大学中日联谊医院 长春 130033
Research on Disease Risk Factors on Structural Equation Model
Dongmei Mu1(),Hui Fa1,Ping Wang1,Jing Sun2
1School of Public Health, Jilin University, Changchun 130021, China
2China-Japan Union Hospital of Jilin University, Changchun 130033, China
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【目的】利用结构方程模型分析客观指标数据, 对与疾病相关的危险因素进行挖掘。【方法】利用文献研究、线性相关分析方法提取疾病危险因素, 使用结构方程模型对这些危险因素进行分析; 使用分类回归树(Classification And Regression Tree, CART)算法构建疾病诊断模型, 利用诊断模型对危险因素进行定性、定量评价及对比分析。【结果】挖掘出9个与疾病相关的危险因素, 经定量评价后, 基于结构方程模型的疾病危险因素诊断模型各项指标均处于较高水平, 且整体性能更好。【局限】实验数据量有限。【结论】基于结构方程模型的疾病危险因素能够提高疾病的早期诊断率, 可以辅助临床决策。

Abstract

[Objective] This paper aims to use the structural equation model to analyze the objective index data and explore the risk factors related to the disease. [Methods] Based on literature research and linear correlation analysis, this paper extracts disease risk factors. Structural Equation modeling was used to analyze these risk factors. The disease diagnosis model was constructed using the classification regression tree (CART) algorithm, and risk factors were qualitatively and quantitatively evaluated and compared using diagnostic models. [Results] Nine risk factors related to disease were discovered. After quantitative evaluation, the indicators of disease risk factors diagnosis model based on Structural Equation Modeling were at a high level, and the overall performance was better. [Limitations] The amount of experimental data is limited, and the amount of data can be expanded to conduct experiments in the future. [Conclusions] Disease risk factors based on structural equation model can improve the early diagnosis rate of disease and can assist clinical decision-making.

Key wordsStructural Equation Modeling    Disease Risk Factors    Data Mining    Disease Diagnosis

 引用本文: 牟冬梅,法慧,王萍,孙晶. 基于结构方程模型的疾病危险因素研究*[J]. 数据分析与知识发现, 2019, 3(4): 80-89. Dongmei Mu,Hui Fa,Ping Wang,Jing Sun. Research on Disease Risk Factors on Structural Equation Model. Data Analysis and Knowledge Discovery, DOI：10.11925/infotech.2096-3467.2018.0631. 链接本文: http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2018.0631
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