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.
Irene Pérez hasn't uploaded this paper.
Let Irene know you want this paper to be uploaded.
