Association, statistical, mathematical and neural approaches for mining breast cancer patterns

被引：71

作者：

Pendharkar, PC

Rodger, JA

Yaverbaum, GJ

Herman, N

Benner, M

机构：

[1] Penn State Univ, Middletown, PA 17057 USA

[2] Univ Pittsburgh, Dept Business, Johnstown, PA 15904 USA

[3] AMP Inc, Harrisburg, PA USA

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 1999年 / 17卷 / 03期

关键词：

data mining; data envelopment analysis; artificial neural networks;

D O I：

10.1016/S0957-4174(99)00036-6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Using several association and classification approaches to study breast cancer patterns, this study illustrates how these approaches can be used to predict and diagnose the occurrence of breast cancer. The results of the study, based on data obtained hom a large medical facility in western Pennsylvania, show that data mining can be a viable tool for breast cancer diagnosis. (C) 1999 Elsevier Science Ltd. All rights reserved.

引用

页码：223 / 232

页数：10