| Biomedical system based on the Discrete Hidden Markov Model using the Rocchio-Genetic approach for the classification of internal carotid artery Doppler signals. | |
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MedLine Citation:
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PMID: 20673596 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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When the maximum likelihood approach (ML) is used during the calculation of the Discrete Hidden Markov Model (DHMM) parameters, DHMM parameters of the each class are only calculated using the training samples (positive training samples) of the same class. The training samples (negative training samples) not belonging to that class are not used in the calculation of DHMM model parameters. With the aim of supplying that deficiency, by involving the training samples of all classes in calculating processes, a Rocchio algorithm based approach is suggested. During the calculation period, in order to determine the most appropriate values of parameters for adjusting the relative effect of the positive and negative training samples, a Genetic algorithm is used as an optimization technique. The purposed method is used to classify the internal carotid artery Doppler signals recorded from 136 patients as well as of 55 healthy people. Our proposed method reached 97.38% classification accuracy with fivefold cross-validation (CV) technique. The classification results showed that the proposed method was effective for the classification of internal carotid artery Doppler signals. |
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Authors:
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Harun Uğuz; Gür Emre Güraksın; Uçman Ergün; Rıdvan Saraçoğlu |
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Publication Detail:
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Type: Journal Article Date: 2010-07-29 |
Journal Detail:
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Title: Computer methods and programs in biomedicine Volume: 103 ISSN: 1872-7565 ISO Abbreviation: Comput Methods Programs Biomed Publication Date: 2011 Jul |
Date Detail:
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Created Date: 2011-06-10 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8506513 Medline TA: Comput Methods Programs Biomed Country: Ireland |
Other Details:
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Languages: eng Pagination: 51-60 Citation Subset: IM |
Copyright Information:
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Copyright © 2010 Elsevier Ireland Ltd. All rights reserved. |
Affiliation:
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Department of Computer Engineering, Selçuk University, Konya, Turkey. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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