An Evolutionary Artificial Neural Network Approach for Breast Cancer Diagnosis

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...

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Bibliographic Details
Main Authors: Lijuan Liu, Mingrong Deng
Format: Conference Proceeding
Language:English
Subjects:
adaptive genetic algorithm
Artificial neural networks
Breast cancer
breast cancer diagnosis
Conference management
Data mining
Economic forecasting
Flowcharts
Genetic algorithms
Genetic mutations
Knowledge management
neural network
Space technology
weights and thresholds
Online Access:Request full text
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Summary: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.
DOI:10.1109/WKDD.2010.148