中国药业2013，Vol.22Issue(14)：28-30,3.
支持向量机在预测鼻咽癌患者5年生存状态中的应用
Application of Support Vector Machine in Predicting 5-Year Survival Status of Patients with Nasopharyngeal Carcinoma
摘要
Abstract
Objective To establish the predictive models of 5-year survival status in the patients with nasopharyngeal carcinoma by using the support vector machine (SVM),and to compare it with the widely applied artificial neural network (ANN) model for exploring the new method for the research of nasopharyngeal carcinoma prognosis.Methods The cinical data in 130 patients with nasopharyngeal carcinoma admitted to our hospital from January 2005 to December 2007 were collected and divided into 2 groups,one group(104 cases) as the training sample for screening the variables and establishing the prediction model and the another group (26 cases) as confirmation sample for evaluating the model effect.The single factor analysis was adopted to screen the variables for establishing the predictive model.Then ANN and SVM were used to establish the predictive models for 5-year survival status in the patients with nasopharyngeal carcinoma.The effect was also evaluated.Results The single factor analysis showed that 12 variables,including age,T stage,N stage,M stage,92 Fuzhou stage,KPS score,destruction of skull base bone,damage of cranial nerves,invasion of parapharyngeal space,time from diagnosis to radiotherapy,treatment effect of nasopharynx and of cervical lymph node,were related with the 5-year survival status (P ＜ 0.05).By the evaluation of confirmation group,the accuracy,sensitivity and specificity of the ANN model were 88.5％,87.5％ and 90.0％ respectively,whereas which of the SVM model were 96.2％,93.8％ and 100％ respectively.Conclusion The model based on SVM could better predict the 5-year survival status in the patients with nasopharyngeal carcinoma,provides a new method to individually predict the prognosis.The efficacy of the SVM model is superior to that of the ANN model.关键词
鼻咽癌/生存状态/支持向量机/人工神经网络Key words
nasopharyngeal carcinoma/survival status/support vector machine/artificial neural network分类
医药卫生引用本文复制引用
高云,杨胜利,何蓉,何兴平,彭明尧,代军,朱江红,胡军,苏敏..支持向量机在预测鼻咽癌患者5年生存状态中的应用[J].中国药业,2013,22(14):28-30,3.基金项目
四川省卫生厅科学研究基金项目,项目编号:100353 （）
攀枝花市科技服务民生行动项目,项目编号:2010cy-s-1(5). （5）
