基于BP神经网络的中医辨证模型构建方法探讨  

The Research on the Construction of the TCM Differentiation Model Based on BP Neural Network

作　　者：徐亮[1] 陈守强[2] 侯建辉[1] 毕文霞[1] 袁锋[3] 

机构地区：[1]山东中医药大学,济南250014 [2]山东中医药大学第二附属医院心脏中心,济南250001 [3]山东管理学院信息工程学院,济南250001

出　　处：《世界中医药》2016年第2期335-338,共4页World Chinese Medicine

基　　金：2014年山东省科技惠民计划项目(编号:2014kjhm0115)

摘　　要：目的:以气虚证辨证模型为例,探讨中医辨证模型构建方法。方法:将684例名老中医医案录入电子病历中,利用其统计功能,创建验案症状表;将验案症状表导入Matlab软件中;利用BP神经网络程序,随机将669例医案作为训练数据,剩余15份病例作为测试数据。结果:测试数据与模型数据之间的绝对误差中,有3例大于0.6,其余12例小于0.3;灵敏度为83.3%,特异性为77.8%,预测一致性为80%。结论:本文以气虚证为例,结合BP神经网络技术,创建了一种中医辨证模型,准确率较高,并为挖掘名老中医辨证经验提供了一条新的途径,值得推广。Objective： To construct a Traditional Chinese Medicine（ TCM） differentiation model by taking qi deficiency syndrome differentiation model as an example. Methods： To input the 684 cases and medication records of TCM distinguished veteran doctors into the electronic medical records management system and build a table of symptoms using its statistical function. Then using BP neutral network to input the symptoms table into Matlab software and take 669 medical records as training data randomly. The last 15 medical records are taken as test data. Results： The absolute error in test data and model data shows that there are 3 cases that are greater than 0. 6,and the other 12 cases were less than 0. 3. The accuracy is 83. 3%,specificity is 77. 8%,and predication consistency is 80%. Conclusion： This research has developed a TCM syndrome differentiation model with high accuracy based on BP neural network,and explored a new way to summarize experience of TCM distinguished veteran doctors. Therefore,it is worthy of popularizing.

关 键 词：辨证模型 BP神经网络 气虚 中医 

分 类 号：R241.4[医药卫生—中医诊断学] R311[医药卫生—中医临床基础]