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WeAidU - a decision support system for myocardial perfusion images using artificial neural networks

Ohlsson, Mattias LU orcid (2004) In Artificial Intelligence in Medicine 30(1). p.49-60
Abstract
This paper presents a computer-based decision support system for automated interpretation of diagnostic heart images (called WeAidU), which is made available via the Internet. The system is based on image processing techniques, artificial neural networks (ANNs) and large well-validated medical databases. We present results using artificial neural networks, and compare with two other classification methods, on a retrospective data set containing 1320 images from the clinical routine. The performance of the artificial neural networks detecting infarction and ischemia in different parts of the heart, measured as areas under the receiver operating characteristic curves, is in the range 0.83-0.96. These results indicate a high potential for the... (More)
This paper presents a computer-based decision support system for automated interpretation of diagnostic heart images (called WeAidU), which is made available via the Internet. The system is based on image processing techniques, artificial neural networks (ANNs) and large well-validated medical databases. We present results using artificial neural networks, and compare with two other classification methods, on a retrospective data set containing 1320 images from the clinical routine. The performance of the artificial neural networks detecting infarction and ischemia in different parts of the heart, measured as areas under the receiver operating characteristic curves, is in the range 0.83-0.96. These results indicate a high potential for the tool as a clinical decision support system. (C) 2003 Elsevier B.V. All rights reserved. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
infarction, myocardial ischemia, myocardial perfusion images, myocardial, computer-assisted, artificial neural networks, diagnosis
in
Artificial Intelligence in Medicine
volume
30
issue
1
pages
49 - 60
publisher
Elsevier
external identifiers
  • wos:000188290200003
  • pmid:14684264
  • scopus:0346218243
ISSN
1873-2860
DOI
10.1016/S0933-3657(03)00050-2
language
English
LU publication?
yes
id
8b86ef57-b396-448c-9019-57f0b2b1ab39 (old id 289568)
date added to LUP
2016-04-01 11:48:54
date last changed
2024-04-22 18:11:22
@article{8b86ef57-b396-448c-9019-57f0b2b1ab39,
  abstract     = {{This paper presents a computer-based decision support system for automated interpretation of diagnostic heart images (called WeAidU), which is made available via the Internet. The system is based on image processing techniques, artificial neural networks (ANNs) and large well-validated medical databases. We present results using artificial neural networks, and compare with two other classification methods, on a retrospective data set containing 1320 images from the clinical routine. The performance of the artificial neural networks detecting infarction and ischemia in different parts of the heart, measured as areas under the receiver operating characteristic curves, is in the range 0.83-0.96. These results indicate a high potential for the tool as a clinical decision support system. (C) 2003 Elsevier B.V. All rights reserved.}},
  author       = {{Ohlsson, Mattias}},
  issn         = {{1873-2860}},
  keywords     = {{infarction; myocardial ischemia; myocardial perfusion images; myocardial; computer-assisted; artificial neural networks; diagnosis}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{49--60}},
  publisher    = {{Elsevier}},
  series       = {{Artificial Intelligence in Medicine}},
  title        = {{WeAidU - a decision support system for myocardial perfusion images using artificial neural networks}},
  url          = {{http://dx.doi.org/10.1016/S0933-3657(03)00050-2}},
  doi          = {{10.1016/S0933-3657(03)00050-2}},
  volume       = {{30}},
  year         = {{2004}},
}