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Application of artificial neural networks in the diagnosis of urological dysfunctions

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Author

  • David Gil
  • Magnus Johnsson
  • Juan Manuel Garcia Chamizo
  • Antonio Soriano Paya
  • Daniel Ruiz Fernandez

Summary, in English

In this article, we evaluate the work out of some artificial neural network models as tools for support in the medical diagnosis of urological dysfunctions. We develop two types of unsupervised and one supervised neural network. This scheme is meant to help the urologists in obtaining a diagnosis for complex multi-variable diseases and to reduce painful and costly medical treatments since neurological dysfunctions are difficult to diagnose. The clinical study has been carried out using medical registers of patients with urological dysfunctions. The proposal is able to distinguish and classify between ill and healthy patients. (C) 2008 Elsevier Ltd. All rights reserved.

Department/s

Publishing year

2009

Language

English

Pages

5754-5760

Publication/Series

Expert Systems with Applications

Volume

36

Issue

3

Document type

Journal article review

Publisher

Elsevier

Topic

  • Computer Science

Keywords

  • Urology
  • Decision support systems
  • Expert systems in medicine
  • Artificial neural networks
  • Artificial intelligence

Status

Published

ISBN/ISSN/Other

  • ISSN: 0957-4174