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Application of artificial neural networks in the diagnosis of urological dysfunctions

Gil, David LU ; Johnsson, Magnus LU ; Chamizo, Juan Manuel Garcia; Paya, Antonio Soriano and Fernandez, Daniel Ruiz (2009) In Expert Systems with Applications 36(3). p.5754-5760
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.
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Urology, Decision support systems, Expert systems in medicine, Artificial neural networks, Artificial intelligence
in
Expert Systems with Applications
volume
36
issue
3
pages
5754 - 5760
publisher
Elsevier
external identifiers
  • wos:000263817100002
  • scopus:58349089446
ISSN
0957-4174
DOI
10.1016/j.eswa.2008.06.065
language
English
LU publication?
yes
id
76b5f9f0-f519-4576-83fb-ed4034437bb5 (old id 1370712)
date added to LUP
2009-05-08 17:36:55
date last changed
2017-08-13 03:38:04
@article{76b5f9f0-f519-4576-83fb-ed4034437bb5,
  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.},
  author       = {Gil, David and Johnsson, Magnus and Chamizo, Juan Manuel Garcia and Paya, Antonio Soriano and Fernandez, Daniel Ruiz},
  issn         = {0957-4174},
  keyword      = {Urology,Decision support systems,Expert systems in medicine,Artificial neural networks,Artificial intelligence},
  language     = {eng},
  number       = {3},
  pages        = {5754--5760},
  publisher    = {Elsevier},
  series       = {Expert Systems with Applications},
  title        = {Application of artificial neural networks in the diagnosis of urological dysfunctions},
  url          = {http://dx.doi.org/10.1016/j.eswa.2008.06.065},
  volume       = {36},
  year         = {2009},
}