Breast cancer diagnosis using Genetically Optimized Neural Network model
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @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