Nature Inspired Clustering Methods in The Electrocardiogram Interpretation Process in Cardiology

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00170436" target="_blank" >RIV/68407700:21230/10:00170436 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Nature Inspired Clustering Methods in The Electrocardiogram Interpretation Process in Cardiology
Original language description
The paper focuses on the field of artificial intelligence techniques and their use in biomedical data processing. It concentrates on the clustering techniques inspired by various ant colonies and other nature concepts. The paper evaluates the use of thefollowing nature inspired methods: Ant Colony inspired Clustering, Ant Colony inspired method for Decision Tree generation, Radial Basis Function Neural Networks with different learning algorithms and compare them to classical approaches, such as k-meansand hierarchical clustering. The methods have been evaluated using the annotated MIT-BIH database. Use of the Dynamic Time Warping measure improved Sensitivity about 0.7 % and Specificity about 0.9 % when compared to classical feature extraction. Thebest-performing method is the agglomerative hierarchical clustering (Se=94.3, Sp=74.1), however it is practically unusable as it is memory and computational demanding.
Czech name
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Czech description
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Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Analysis of Biomedical Signals and Images, BIOSIGNAL 2010, Proceedings
ISBN
978-80-214-4106-4
ISSN
1211-412X
e-ISSN
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Number of pages
5
Pages from-to
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Publisher name
Brno University of Technology
Place of publication
Brno
Event location
Brno
Event date
Jun 27, 2010
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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