Breast cancer prediction using a neural network model

被引：0

作者：

Nastac, I ^{[1
]}

Jalava, P ^{[1
]}

Collan, M ^{[1
]}

Collan, Y ^{[1
]}

Kuopio, T ^{[1
]}

Back, B ^{[1
]}

机构：

[1] Abo Akad Univ, TUCS, Turku, Finland

来源：

Soft Computing with Industrial Applications, Vol 17 | 2004年 / 17卷

关键词：

ER; neural network; training; test; prediction; cutpoint; efficiency; sensitivity; specificity;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper reports results on using an artificial Moral network (ANN) for predicting the estrogen receptor (ER) status, which is not always available, but has a place in therapy selection of breast cancer. Our results show that in more than two thirds of the cases, the ANN is able to predict the correct ER status. An optimum neural architecture was researched, and optimal cutpoint for prediction selected on the basis of clinical data.

引用

页码：423 / 428

页数：6

共 12 条

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