Prediction model building and feature selection with support vector machines in breast cancer diagnosis
Prediction model building and feature selection with support vector machines in breast cancer diagnosis
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DOI：
10.1016/j.eswa.2006.09.041
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发表时间：
2008-01-01
影响因子：
8.5
通讯作者：
Chen, Mu-Chen
中科院分区：
文献类型：
--
作者：
Huang, Cheng-Lung;Liao, Hung-Chang;Chen, Mu-Chen
乳腺癌是台湾年轻女性面临的一个严重问题。一些医学研究证明DNA病毒是与人类癌症密切相关的高危因素之一。本研究中研究了五种DNA病毒：HSV-1（单纯疱疹病毒1型）、EBV（EB病毒）、CMV（巨细胞病毒）、HPV（人类）。乳头瘤病毒）和HHV-8（人疱疹病毒-8）。本研究的目的是获得乳腺肿瘤和DNA病毒的生物信息学信息，建立乳腺癌和纤维腺瘤的准确诊断模型。支持向量机（SVM）具有更高的准确诊断能力，这一点已得到越来越多的证实。因此，本研究建构一个混合SVM为基础的策略与特征选择，以提供诊断之间的乳腺癌和纤维腺瘤，并找到乳腺癌的重要危险因素。结果表明，JHSV-1、HHV-8}或{HSV-1、HHV-8、CMV）是最重要的特征，诊断模型取得了较高的分类准确率，平均总体命中率为86%。本文还建立了线性判别分析（LDA）诊断模型. LDA模型表明，{HSV-1，HHV-8，EBV}或{HSV-1，HHV-8}是与基于SVM的分类器相似的显著因子。然而，基于SVM的分类器的分类精度略优于LDA的负命中率，正命中率，和整体命中率。(c)2006爱思唯尔有限公司保留所有权利。
Breast cancer is a serious problem for the young women of Taiwan. Some medical researches have proved that DNA viruses are one of the high-risk factors closely related to human cancers. Five DNA viruses are studied in this research: specific types of HSV-1 (herpes simplex virus type 1), EBV (Epstein-Barr virus), CMV (cytomegalovirus), HPV (human. papillomavirus), and HHV-8 (human herpesvirus-8). The purposes of this study are to obtain the bioinformatics about breast tumor and DNA viruses, and to build an accurate diagnosis model about breast cancer and fibroadenoma. Research efforts have reported with increasing confirmation that the support vector machine (SVM) has a greater accurate diagnosis ability. Therefore, this study constructs a hybrid SVM-based strategy with feature selection to render a diagnosis between the breast cancer and fibroadenoma and to find the important risk factor for breast cancer. The results show that JHSV-l, HHV-8} or {HSV-1, HHV-8, CMV) are the most important features and that the diagnosis model achieved high classification accuracy, at 86% of average overall hit rate. A Linear discriminate analysis (LDA) diagnosis model is also constructed in this study. The LDA model shows that {HSV-1, HHV-8, EBV} or {HSV-1, HHV-8} are significant factors which are similar to that of the SVM-based classifier. However, the classificatory accuracy of the SVM-based classifier is slightly better than that of LDA in the negative hit ratio, positive hit ratio, and overall hit ratio. (c) 2006 Elsevier Ltd. All rights reserved.