文章基本信息

标题：PREDICTION OF SURVIVAL IN PATIENTS WITH BREAST CANCER USING THREE ARTIFICIAL INTELLIGENCE TECHNIQUES
本地全文：下载
作者：CHENG-TAO YU ; CHENG-MIN CHAO ; BOR-WEN CHENG 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2014
卷号：60
期号：1
出版社：Journal of Theoretical and Applied
摘要：As medical technology advances, has accumulated a large number of health-related data. Faced with increasingly complex analytical requirements, predictive data mining has become an essential instrument for hospital management and medical research. In this study, the breast cancer dataset is collected from a regional teaching hospital in central Taiwan between 2002 and 2009. The prognostic factors composed of 8 attributes including 967 subjects, of which 861 are survival after treatment. The three techniques, artificial neural networks (ANNs), support vector machine (SVM) and Bayesian classifier, have been discussed which is used to investigated and evaluated for predicting breast cancer survival. As can be seen from the results, the prediction accuracy of a 10-fold cross validation is 90.31%, 89.79% and 88.64%, respectively. Classification results of SVM are slightly better as compared to ANN and Bayesian classifier, however, from a relatively low variance, the results show that the SVM will be the best prognosis in clinical practice.
关键词：Breast Cancer; Bayesian classifier; Support vector machines (SVM); Artificial Neural Networks (ANNs)