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 complica-tions 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 sup-port 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
Key words
type 2 diabetes/microvascular complications/disease prediction model/clinical data processing/real-world data
维普
万方数据