空军军医大学学报2024，Vol.45Issue(8)：930-934,5.DOI:10.13276/j.issn.2097-1656.2024.08.017
糖尿病患者动脉粥样硬化发病风险预测模型比较研究
A comparative study of risk prediction models for atherosclerosis in patients with diabetes mellitus
摘要
Abstract
Objective To analyze and compare the application of LightGBM and random forest machine learning model in the risk prediction model of atherosclerosis in diabetic patients.Methods Based on the public data set of National Population Health Data Center,the risk prediction model of atherosclerosis was established and compared with LightGBM and random forest algorithms.Results The machine learning model of LightGBM and random forest was used to analyze atherosclerosis.It was found that the accuracy of random forest was 0.624 2,area under the curve(AUC)was 0.671 8,and precision was 0.629 7,which were all higher than those of LightGBM.However,the recall rate of LightGBM and F1 score of LightGBM were 0.756 7 and 0.665 2,which were higher than those of random forest,but both of them had good prediction effects for atherosclerosis.Conclusion In the prediction model of atherosclerosis,random forest has a higher accuracy,AUC and precision,while LightGBM has a higher recall rate and F1 score.In general,both of them can accurately predict atherosclerosis,which can be applied to clinical practice and provide useful reference for the related research of clinical auxiliary diagnosis of diabetic complications.关键词
糖尿病/动脉粥样硬化/机器学习/预测分析Key words
diabetes mellitus/atherosclerosis/machine learning/prediction analysis分类
医药卫生引用本文复制引用
韩政元,杨紫薇,赵陆洋,李林怿,刘奎,万毅..糖尿病患者动脉粥样硬化发病风险预测模型比较研究[J].空军军医大学学报,2024,45(8):930-934,5.基金项目
国家自然科学基金面上项目(82073663) （82073663）
