中国医疗设备2016，Vol.31Issue(3)：33-38,69,7.DOI:10.3969/j.issn.1674-1633.2016.03.006
基于Logistic回归和随机森林算法的2型糖尿病并发视网膜病变风险预测及对比研究
Risk Prediction and Comparitive Research of Type 2 Diabetes Mellitus Complicated with Retinopathy based on Logistic Regression and Random Forest Algorithm
摘要
Abstract
Objective To analyze the relevant factors of type 2 diabetes mellitus complicated with retinopathy and to construct the risk prediction model based on machine learning, the random forest algorithm, and the Logistic regression algorithm based on the epidemiological design.Methods To analyze the data from the electronic medical record of patients with type 2 diabetes mellitus complicated with retinopathy in the General Hospital of PLA during 2011-2013. The main focus was on the diagnostic data of diabetes mellitus, the glycosylated data, and biochemical examination data. The prediction effect of the two models were compared with the Logistic regression algorithm and random forest algorithm according the area under the ROC curve.Results Among the 39 variables in the the random forest models, blood glucose control (HbAlc), fasting glucose, urea, creatinine, uric acid, age, coronary heart disease (CHD), and chronic kidney disease (CKD) had higher scores and were of significant clinical explanations. The Logistic regression model ifnally in corporated six factors: sex, HbAlc, CKD, CHD, myocardial infarction, and cancer. The area under the ROC curve showed that the prediction effect of the random forest model was better than the Logistic regression Model.Conclusion The research provided grading of the significance of different variable, which to a certain extent provides guidance for the early diagnosis of type 2 diabetes mellitus complicated with retinopathy and the optimization of clinical diagnosis lfow.关键词
2型糖尿病/视网膜病变/关联因素/风险预测/随机森林算法/Logistic回归算法Key words
type 2 diabetes mellitus/retinopathy/correlative factor/risk prediction/random forestalgorithm/Logistic regressionalgorithm分类
信息技术与安全科学引用本文复制引用
曹文哲,应俊,陈广飞,周丹..基于Logistic回归和随机森林算法的2型糖尿病并发视网膜病变风险预测及对比研究[J].中国医疗设备,2016,31(3):33-38,69,7.基金项目
国家自然科学基金（61501518）。 （）
