LVQ神经网络在临床辅助鉴别诊断中的应用研究  

Application of Clinical Auxiliary Differential Diagnosis Based on Learning Vector Quantization Neural Network

作　　者：李文念[1] 孙卫[2] 李颖[1] 俞思伟[3] 

机构地区：[1]中国科学技术信息研究所,北京市海淀区复兴路15号100038 [2]科学出版社,北京市东黄城根北街16号100717 [3]武汉大学中南医院

出　　处：《中国数字医学》2013年第5期72-75,81,共5页China Digital Medicine

基　　金："十二五"科技支撑计划-面向外文科技知识组织体系的大规模语义计算关键技术研究(编号:2011BAH10B04-04)~~

摘　　要：选取协和医院64例结节病和42例肺结核病病历作为数据样本,探究建立基于LVQ神经网络的临床辅助鉴别诊断模型以实现这两种疾病的鉴别诊断,测试结果总体确诊率达到87.50%,并与BP神经网络算法结果相对比。实证分析结果表明,该模型对疾病的辅助鉴别诊断有着良好的应用效果,利用LVQ神经网络实现疾病的临床辅助鉴别诊断是有效的。This paper put forward a clinical auxiliary differential diagnosis model based on learning vector quantization（LVQ） neural network. An experiment was designed with the data sample of 106 medical records consisting of 64 patients with sarcoidosis and 42 patients with tuberculosis from the Union Hospital. The empirical analysis results show that the test results have an overall positive rate of 87.50%, and the model for the clinical auxiliary differential diagnosis of diseases has a good application effect. The clinical auxiliary differential diagnosis based on LVQ neural network is appropriate, and it can make differential diagmosis of diseases effectively.

关 键 词：LVQ神经网络 鉴别诊断 结节病 肺结核 

分 类 号：R445.1[医药卫生—影像医学与核医学]