An Evolutionary Artificial Neural Network Approach for Breast Cancer Diagnosis

Author

Liu, Lijuan ; Deng, Mingrong

Author_Institution

Sch. of Manage., Zhejiang Univ., Hangzhou, China

fYear

2010

fDate

9-10 Jan. 2010

Firstpage

593

Lastpage

596

Abstract

In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with an evolutionary artificial neural network approach based on adaptive genetic algorithm with strong macro-search capability and global optimization, which was used to optimize initial weights and thresholds of the network. Experimental results had better precision and much lower computational cost compared to the literature related to this concept in the Wisions breast cancer data set.

Keywords

cancer; genetic algorithms; medical image processing; neural nets; Wisions breast cancer data set; adaptive genetic algorithm; artificial neural network; breast cancer diagnosis; computational cost; global optimization; macro-search capability; women; Artificial neural networks; Breast cancer; Conference management; Data mining; Economic forecasting; Flowcharts; Genetic algorithms; Genetic mutations; Knowledge management; Space technology; adaptive genetic algorithm; breast cancer diagnosis; neural network; weights and thresholds;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on

Conference_Location

Phuket

Print_ISBN

978-1-4244-5397-9

Electronic_ISBN

978-1-4244-5398-6

Type

conf

DOI

10.1109/WKDD.2010.148

Filename

5432472