A hybrid automated detection system based on least square support vector machine classifier and k-NN based weighted pre-processing for diagnosing of macular disease

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dc.contributor.authorPolat, Kemal
dc.contributor.authorKara, Sadik
dc.contributor.authorGuven, Aysegul
dc.contributor.authorGunes, Salih
dc.date.accessioned2020-03-26T17:16:55Z
dc.date.available2020-03-26T17:16:55Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.description8th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA) -- APR 11-14, 2007 -- Warsaw Univ Technol, Warsaw, POLANDen_US
dc.description.abstractIn this paper, we proposed a hybrid automated detection system based least square support vector machine (LSSVM) and k-NN based weighted pre-processing for diagnosing of macular disease from the pattern electroretinography (PERG) signals. k-NN based weighted pre-processing is pre-processing method, which is firstly proposed by us. The proposed system consists of two parts: k-NN based weighted pre-processing used to weight the PERG signals and LSSVM classifier used to distinguish between healthy eye and diseased eye (macula diseases). The performance and efficiency of proposed system was conducted using classification accuracy and 10-fold cross validation. The results confirmed that a hybrid automated detection system based on the LSSVM and k-NN based weighted pre-processing has potential in detecting macular disease. The stated results show that proposed method could point out the ability of design of a new intelligent assistance diagnosis system.en_US
dc.description.sponsorshipScientific Research Project of Selcuk UniversitySelcuk University [05401069]en_US
dc.description.sponsorshipThis study has been supported by Scientific Research Project of Selcuk University (Project No: 05401069).en_US
dc.identifier.endpage+en_US
dc.identifier.isbn978-3-540-71590-0
dc.identifier.issn0302-9743en_US
dc.identifier.issn1611-3349en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage338en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21172
dc.identifier.volume4432en_US
dc.identifier.wosWOS:000246098200038en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGER-VERLAG BERLINen_US
dc.relation.ispartofADAPTIVE AND NATURAL COMPUTING ALGORITHMS, PT 2en_US
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleA hybrid automated detection system based on least square support vector machine classifier and k-NN based weighted pre-processing for diagnosing of macular diseaseen_US
dc.typeConference Objecten_US

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