Application of artificial neural networks in the diagnosis of urological dysfunctions

Research output: Contribution to journalReview article

Abstract

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.

Details

Authors
  • David Gil
  • Magnus Johnsson
  • Juan Manuel Garcia Chamizo
  • Antonio Soriano Paya
  • Daniel Ruiz Fernandez
Organisations
External organisations
  • University of Alicante
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Computer Science

Keywords

  • Urology, Decision support systems, Expert systems in medicine, Artificial neural networks, Artificial intelligence
Original languageEnglish
Pages (from-to)5754-5760
JournalExpert Systems with Applications
Volume36
Issue number3
Publication statusPublished - 2009
Publication categoryResearch
Peer-reviewedYes