Artificial Neural Networks for Diagnoses of Dysfunctions in Urology

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.

Johnsson, MagnusLund University,Lunds universitet,Kognitionsvetenskap,Filosofiska institutionen,Institutioner,Humanistiska och teologiska fakulteterna,Cognitive Science,Department of Philosophy,Departments,Joint Faculties of Humanities and Theology(Swepub:lu)lucs-mj0 (author)
Soriano Paya, A (author)
Ruiz Fernandez, D (author)
Azevedo, Luis (editor)
Londral, Ana (editor)
KognitionsvetenskapFilosofiska institutionen (creator_code:org_t)

In:Proceedings of the First International Conference on Health Informatics2, s. 191-1969789898111166

About the subject

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Computer Vision ...

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