Prediction of Microvascular Complications in Type 2 Diabetes Mellitus Based on Deep Belief Network
10.3969/j.issn.1673-6036.2024.07.012
- VernacularTitle:基于深度置信网络的2型糖尿病微血管并发症预测
- Author:
Ruiyao LI
1
;
Jingyi XU
;
Haoyu DAI
;
Huiwen SUN
;
Ying BAO
;
Lvchun HUA
;
Tianxing WU
Author Information
1. 南京鼓楼医院信息管理处 南京 210008
- Keywords:
type 2 diabetes;
microvascular complications;
disease prediction model;
clinical data processing;
real-world data
- From:
Journal of Medical Informatics
2024;45(7):68-73
- CountryChina
- Language:Chinese
-
Abstract:
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.
