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ARTMED
2002

An evolutionary artificial neural networks approach for breast cancer diagnosis

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An evolutionary artificial neural networks approach for breast cancer diagnosis
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breast cancer. The approach is named memetic pareto artificial neural network (MPANN). artificial neural networks could be used to improve the work of medical practitioners in the diagnosis of breast cancer. Their abilities to approximate nonlinear functions and capture complex relationships in the data are instrumental abilities which could support the medical domain. We compare our results against an evolutionary programming approach and standard backpropagation and we show experimentally that MPANN has better generalization and much lower computational cost. Keywords Pareto optimization, differential evolution, artificial neural networks, breast cancer.
Hussein A. Abbass
Added 16 Dec 2010
Updated 16 Dec 2010
Type Journal
Year 2002
Where ARTMED
Authors Hussein A. Abbass
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