An expert system for detection of breast cancer based on association rules and neural network

Authors:
Murat Karabatak;M. Cevdet Ince
Affiliations:
Fırat University, Department of Electronics and Computer Science, 23119 Elazig, Turkey;Fırat University, Department of Electric-Electronics Engineering, 23119 Elazig, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

Citing 8
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Abstract

This paper presents an automatic diagnosis system for detecting breast cancer based on association rules (AR) and neural network (NN). In this study, AR is used for reducing the dimension of breast cancer database and NN is used for intelligent classification. The proposed AR+NN system performance is compared with NN model. The dimension of input feature space is reduced from nine to four by using AR. In test stage, 3-fold cross validation method was applied to the Wisconsin breast cancer database to evaluate the proposed system performances. The correct classification rate of proposed system is 95.6%. This research demonstrated that the AR can be used for reducing the dimension of feature space and proposed AR+NN model can be used to obtain fast automatic diagnostic systems for other diseases.