基于深度置信网络的2型糖尿病微血管并发症预测  

Prediction of Microvascular Complications in Type 2 Diabetes Mellitus Based on Deep Belief Network

作　　者：李瑞瑶 许婧怡 戴浩宇 孙慧文 鲍瀛 华履春 吴天星[2,4] LI Ruiyao;XU Jingyi;DAI Haoyu;SUN Huiwen;BAO Ying;HUA Lvchun;WU Tianxing(Department of Information Management,Nanjing Drum Tower Hospital,Nanjing 210008,China;School of Computer Science and Engineering,Southeast University,Nanjing 211189,China;Department of Geriatrics,Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University,Nanjing 210008,China;Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications(Southeast University),Ministry of Education,Nanjing 211189,China)

机构地区：[1]南京鼓楼医院信息管理处,南京210008 [2]东南大学计算机科学与工程学院,南京211189 [3]南京医科大学鼓楼临床医学院老年科,南京210008 [4]新一代人工智能技术与交叉应用教育部重点实验室,南京211189

出　　处：《医学信息学杂志》2024年第7期68-73,共6页Journal of Medical Informatics

基　　金：国家自然科学基金面上项目(项目编号:62376058);江苏省医院协会医院管理创新研究课题(项目编号:JSYGY-3-2023-616);南京大学中国医院改革发展研究院课题项目(项目编号:NDYGN2023021)。

摘　　要：目的/意义基于真实世界数据构建预测模型,实现对2型糖尿病微血管病变的预测和早期筛查。方法/过程以南京鼓楼医院10年间真实世界数据为资料,将检验检查结果、病历文书等纳入考量,构建基于粒子群算法优化深度置信网络的2型糖尿病微血管并发症预测模型。结果/结论该模型能够预测2型糖尿病微血管并发症,性能优于随机森林、支持向量机基准模型,为真实世界数据疾病预测模型研究提供借鉴。Purpose/Significance A prediction model is constructed based on real-world data to achieve prediction and early screening of type 2 diabetic microvascular complications.Method/Process Based on the real world data of Nanjing Drum Tower Hospital in the past 10 years,a particle swarm optimization based deep belief network(PSO-DBN)prediction model for microvascular complications in type 2 diabetes mellitus is constructed by taking test results and medical record documents into consideration.Result/Conclusion The PSO-DBN model can predict diabetic microvascular complications,and the performance is better than that of random forest and support vector machine(SVM)benchmark models,it provides references for the research of disease prediction model of real-world data.

关 键 词：2型糖尿病 微血管并发症 疾病预测模型 临床数据处理 真实世界数据 

分 类 号：R-058[医药卫生]