Risk Prediction and Comparitive Research of Type 2 Diabetes Mellitus
Complicated with Retinopathy based on Logistic Regression and
Random Forest Algorithm
CAO Wen-zhea, YING Juna,CHEN Guang-feia, ZHOU Danb
a.Department of Biomedical Engineering;
b.Department of Medical Management,
General Hospital of PLA, Beijing 100853,
China
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 finally 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 flow.
曹文哲a，应俊a，陈广飞a，周丹b. 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.
CAO Wen-zhea, YING Juna,CHEN Guang-feia, ZHOU Danb. Risk Prediction and Comparitive Research of Type 2 Diabetes Mellitus
Complicated with Retinopathy based on Logistic Regression and
Random Forest Algorithm. China Medical Devices, 2016, 31(3): 33-38.
