Document Detail


A neuro-fuzzy algorithm for diagnosis of coronary artery stenosis.
MedLine Citation:
PMID:  8904284     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In this paper a method of fuzzy decision making applied to diagnosis of coronary artery stenosis is presented. The method uses a neural network approach for the diagnosis of stenosis in the three main coronary arteries (left anterior descending, right coronary artery, and circumflex). First, the knowledge base domain, 201Tl scintigram training data, is explained and the method of preprocessing the original heart images is given. Next, the method of dealing with the uncertainties present in the data using the fuzzy approach is outlined. Finally, the algorithm and the results are discussed and compared with other approaches.
Authors:
L M Sztandera; L S Goodenday; K J Cios
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Computers in biology and medicine     Volume:  26     ISSN:  0010-4825     ISO Abbreviation:  Comput. Biol. Med.     Publication Date:  1996 Mar 
Date Detail:
Created Date:  1997-02-12     Completed Date:  1997-02-12     Revised Date:  2007-11-14    
Medline Journal Info:
Nlm Unique ID:  1250250     Medline TA:  Comput Biol Med     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  97-111     Citation Subset:  IM    
Affiliation:
Department of Computer Science, Philadelphia College of Textiles and Science, PA 19144, USA.
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Case-Control Studies
Coronary Disease / radionuclide imaging*
Exercise Test
Fuzzy Logic*
Humans
Image Interpretation, Computer-Assisted / methods*
Neural Networks (Computer)*
Reproducibility of Results
Sensitivity and Specificity
Thallium Radioisotopes / diagnostic use
Grant Support
ID/Acronym/Agency:
1 P41 RR06009/RR/NCRR NIH HHS
Chemical
Reg. No./Substance:
0/Thallium Radioisotopes

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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