基于C5.0算法的胃癌生存预测模型研究  

Gastric cancer prediction model based on C5.0 classification algorithm

作　　者：黄志刚[1] 刘虹[1] 刘娟[1] 张岐山[1] HUANG Zhigang LIU Hong LIU Juan ZHANG Qishan(School of Economics and Management, Fuzhou University, Fuzhou 350116)

机构地区：[1]福州大学经济与管理学院,福州350116

出　　处：《南京信息工程大学学报（自然科学版）》2017年第4期406-410,共5页Journal of Nanjing University of Information Science & Technology（Natural Science Edition）

基　　金：国家自然科学基金(71473039)

摘　　要：我国的胃癌发病率高,每年新增胃癌患者占全世界每年新增数量的42%,胃癌成为我国恶性肿瘤防控的重点.本文针对胃癌数据的特征,给出数据预处理和集成方法;采用C5.0分类算法,构建了胃癌生存预测模型,并首次采用美国癌症研究所的SEER数据库进行预测实验.实验结果表明:C5.0预测的精确度、特异性均高于BP-神经网络算法;胃癌患者的出生地点与最终的存活状态之间存在较强的相关性.该研究是数据挖掘技术在医学领域的一个实际应用,对胃癌的临床诊断具有一定的参考价值,可为医生制定合理的治疗和预防方案提供一定参考.The incidence of gastric cancer is very high in China,and the number of new patients diagnosed with gastric cancer accounts for 42% of that of the whole world every year,so gastric cancer has become the focus of the prevention and control of malignant tumors in China.In this paper,the C5.0 classification algorithm is used to predict the survival rate of gastric cancer,and experiments are carried out using the SEER database of the American National Cancer Institute.The data preprocessing and data integration methods are given according to the unbalanced characteristics of gastric cancer record data.The prediction experimental results show that,the accuracy and specificity of C5.0 algorithm are high compared with BP-neural network method; and there is an obvious correlation between birth place and survival state of gastric cancer patients.This study is a practical application of data mining technology in the field of medicine,which has certain reference value for the clinical diagnosis of gastric cancer; it can provide reference for doctors to formulate reasonable treatment and prevention program.

关 键 词：数据挖掘 C5.0分类算法 胃癌 生存预测 SEER数据库 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]