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Employment and Comparison of Different Artificial Neural Networks for Epilepsy Diagnosis from EEG Signals
In this study, it has been intended to analyze Electroencephalography (EEG) signals by Wavelet Transform (WT) for diagnosis of epilepsy, to employ various Artificial Neural Networks (ANNs) for the signals’ automatic classification. Furthermore, carrying out a performance comparison has been aimed. T...
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Published in: | Journal of medical systems 2012-02, Vol.36 (1), p.347-362 |
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description | In this study, it has been intended to analyze Electroencephalography (EEG) signals by Wavelet Transform (WT) for diagnosis of epilepsy, to employ various Artificial Neural Networks (ANNs) for the signals’ automatic classification. Furthermore, carrying out a performance comparison has been aimed. Three EEG signals have been decomposed into frequency sub bands by WT and the feature vectors have been extracted from these sub bands. In order to reduce the sizes of the extracted feature vectors, Principal Component Analysis (PCA) method has been applied when necessary and these feature vectors have been classified by five different ANNs as either epileptic or healthy. The performance evaluation has been carried out by conducting ROC analysis for the used ANN models that and their comparisons have also been included. |
doi_str_mv | 10.1007/s10916-010-9480-5 |
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The performance evaluation has been carried out by conducting ROC analysis for the used ANN models that and their comparisons have also been included.</description><identifier>ISSN: 0148-5598</identifier><identifier>EISSN: 1573-689X</identifier><identifier>DOI: 10.1007/s10916-010-9480-5</identifier><identifier>PMID: 20703714</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Electroencephalography ; Electroencephalography - methods ; Epilepsy ; Epilepsy - diagnosis ; Health Informatics ; Health Sciences ; Humans ; Medical diagnosis ; Medicine ; Medicine & Public Health ; Neural networks ; Neural Networks (Computer) ; Original Paper ; Principal Component Analysis ; Principal components analysis ; ROC Curve ; Signal Processing, Computer-Assisted ; Statistics for Life Sciences ; Wavelet Analysis ; Wavelet transforms</subject><ispartof>Journal of medical systems, 2012-02, Vol.36 (1), p.347-362</ispartof><rights>Springer Science+Business Media, LLC 2010</rights><rights>Springer Science+Business Media, LLC 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c403t-12dc794c155d07f22e77398ef4d40b623621bbb55d6a26ecc102e2398fdc05463</citedby><cites>FETCH-LOGICAL-c403t-12dc794c155d07f22e77398ef4d40b623621bbb55d6a26ecc102e2398fdc05463</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20703714$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sezer, Esma</creatorcontrib><creatorcontrib>Işik, Hakan</creatorcontrib><creatorcontrib>Saracoğlu, Esra</creatorcontrib><title>Employment and Comparison of Different Artificial Neural Networks for Epilepsy Diagnosis from EEG Signals</title><title>Journal of medical systems</title><addtitle>J Med Syst</addtitle><addtitle>J Med Syst</addtitle><description>In this study, it has been intended to analyze Electroencephalography (EEG) signals by Wavelet Transform (WT) for diagnosis of epilepsy, to employ various Artificial Neural Networks (ANNs) for the signals’ automatic classification. 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subjects | Electroencephalography Electroencephalography - methods Epilepsy Epilepsy - diagnosis Health Informatics Health Sciences Humans Medical diagnosis Medicine Medicine & Public Health Neural networks Neural Networks (Computer) Original Paper Principal Component Analysis Principal components analysis ROC Curve Signal Processing, Computer-Assisted Statistics for Life Sciences Wavelet Analysis Wavelet transforms |
title | Employment and Comparison of Different Artificial Neural Networks for Epilepsy Diagnosis from EEG Signals |
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