Artificial Neural Networks for Diagnoses of Dysfunctions in Urology
Author
Editor
- Luis Azevedo
- Ana Londral
Summary, in English
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.
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.
Department/s
Publishing year
2008
Language
English
Pages
191-196
Publication/Series
Proceedings of the First International Conference on Health Informatics
Volume
2
Document type
Conference paper
Publisher
SciTePress
Topic
- Computer Vision and Robotics (Autonomous Systems)
Conference name
Healthinf 2008
Conference date
2008-01-28 - 2008-01-31
Conference place
Madeira, Portugal
Status
Published
ISBN/ISSN/Other
- ISBN: 978-989-8111-16-6