Artificial neural networks for diagnoses of dysfunctions in urology

David Gil Mendez, Magnus Johnsson, Antonio Soriano Paya, Daniel Ruiz Fernandez

Forskningsoutput: KonferensbidragArbetsdokument (paper)Peer review

1 Citeringar (Scopus)

Sammanfattning

In this article we evaluate the work out of artificial neural networks as tools for helping and support in the medical diagnosis. In particular we compare the usability of one supervised and two unsupervised neural network architectures for medical diagnoses of lower urinary tract dysfunctions. The purpose is to develop a system that aid urologists in obtaining diagnoses, which will yield improved diagnostic accuracy and lower medical treatment costs. The clinical study has been carried out using the medical registers of patients with dysfunctions in the lower urinary tract. The current system is able to distinguish and classify dysfunctions as areflexia, hyperreflexia, obstruction of the lower urinary tract and patients free from dysfunction.

OriginalspråkEngelska
Sidor191-196
Antal sidor6
StatusPublicerad - 2008
Evenemang1st International Conference on Health Informatics, HEALTHINF 2008 - Funchal, Madeira, Portugal
Varaktighet: 2008-jan.-282008-jan.-31

Konferens

Konferens1st International Conference on Health Informatics, HEALTHINF 2008
Land/TerritoriumPortugal
OrtFunchal, Madeira
Period08-01-2808-01-31

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