| Classification of mitral insufficiency and stenosis using MLP neural network and neuro-fuzzy system. | |
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MedLine Citation:
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PMID: 15527030 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Cardiac Doppler signals recorded from mitral valve of 60 patients were transferred to a personal computer by using a 16-bit sound card. The power spectral density (PSD) was applied to the recorded signal from each patient. In order to do a good interpretation and rapid diagnosis, PSD values classified using multilayer perceptron (MLP) and neuro-fuzzy system. Our findings demonstrated that 93.33% classification success rate was obtained from MLP, 90% classification success rate was obtained from neuro-fuzzy system. The classification results show that MLP offers best results in the case of diagnosis. |
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Authors:
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Necaattin Barýpçý; Uçman Ergün; Erdoğan Ilkay; Selami Serhatlýoğlu; Firat Hardalaç; Inan Güler |
Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Journal of medical systems Volume: 28 ISSN: 0148-5598 ISO Abbreviation: J Med Syst Publication Date: 2004 Oct |
Date Detail:
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Created Date: 2004-11-05 Completed Date: 2005-02-24 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 7806056 Medline TA: J Med Syst Country: United States |
Other Details:
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Languages: eng Pagination: 423-36 Citation Subset: IM |
Affiliation:
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Department of Electronic and Computer Education, Faculty of Technical Education, Gazi University, Ankara, Turkey. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Diagnosis, Computer-Assisted
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methods* Echocardiography, Doppler Fuzzy Logic* Humans Mitral Valve Insufficiency / classification*, ultrasonography Mitral Valve Stenosis / classification*, ultrasonography United States |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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