Neural networks versus genetic algorithms as medical classifiers

Authors:
Oscar Marín;Irene Pérez;Daniel Ruiz;Antonio Soriano;Joaquin D. García
Affiliations:
Department of Computer Technology, University of Alicante, Alicante, Spain;Department of Computer Technology, University of Alicante, Alicante, Spain;Department of Computer Technology, University of Alicante, Alicante, Spain;Department of Computer Technology, University of Alicante, Alicante, Spain;Department of Computer Technology, University of Alicante, Alicante, Spain
Venue:
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
Year:
2011

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Abstract

In this article we want to assess the feasibility of using genetic algorithms as classifiers that could be used in clinical decision support systems, for urological diseases diagnosis in our case. The use of artificial neural networks is more common in this field, and we have previously tested their use with the same purpose. At the end of the document we compare the obtained results using genetic algorithms and two different artificial neural networks implementations. The obtained accuracy rates show that genetic algorithms could be a useful tool to be used in the clinical decision support systems field.