Breast cancer diagnosis using Genetically Optimized Neural Network model

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@Article{Bhardwaj:2015:ESA,

• author = "Arpit Bhardwaj and Aruna Tiwari",
• title = "Breast cancer diagnosis using Genetically Optimized Neural Network model",
• journal = "Expert Systems with Applications",
• volume = "42",
• number = "10",
• pages = "4611--4620",
• year = "2015",
• ISSN = "0957-4174",
• DOI = "doi:10.1016/j.eswa.2015.01.065",
• URL = "http://www.sciencedirect.com/science/article/pii/S0957417415000883",
• abstract = "One in every eight women is susceptible to breast cancer, at some point of time in her life. Early detection and effective treatment is the only rescue to reduce breast cancer mortality. Accurate classification of a breast cancer tumour is an important task in medical diagnosis. Machine learning techniques are gaining importance in medical diagnosis because of their classification capability. In this paper, we propose a new, Genetically Optimised Neural Network (GONN) algorithm, for solving classification problems. We evolve a neural network genetically to optimize its architecture (structure and weight) for classification. We introduce new crossover and mutation operators which differ from standard crossover and mutation operators to reduce the destructive nature of these operators. We use the GONN algorithm to classify breast cancer tumors as benign or malignant. To demonstrate our results, we had taken the WBCD database from UCI Machine Learning repository and compared the classification accuracy, sensitivity, specificity, confusion matrix, ROC curves and AUC under ROC curves of GONN with classical model and classical back propagation model. Our algorithm gives classification accuracy of 98.24percent, 99.63percent and 100percent for 50-50, 60-40, 70-30 training-testing partition respectively and 100percent for 10 fold cross validation. The results show that our approach works well with the breast cancer database and can be a good alternative to the well-known machine learning methods.",
• keywords = "genetic algorithms, genetic programming, Genetically Optimised Neural Network, Artificial Neural Network, Modified Crossover Operator",

}

Genetic Programming entries for Arpit Bhardwaj Aruna Tiwari

Citations