A New Method to Medical Diagnosis: Artificial Immune Recognition System (Airs) With Fuzzy Weighted Pre-Processing and Application to Ecg Arrhythmia

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dc.contributor.authorPolat, Kemal
dc.contributor.authorŞahan, Seral
dc.contributor.authorGüneş, Salih
dc.date.accessioned2020-03-26T17:02:57Z
dc.date.available2020-03-26T17:02:57Z
dc.date.issued2006
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractChanges in the normal rhythm of a human heart may result in different cardiac arrhythmias, which may be immediately fatal or cause irreparable damage to the heart sustained over long periods of time. The ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment. Artificial immune systems (AISs) is a new but effective branch of artificial intelligence. Among the systems proposed in this field so far, artificial immune recognition system (AIRS), which was proposed by A. Watkins, has showed an effective and intriguing performance on the problems it was applied. Previously, AIRS was applied a range of problems including machine-learning benchmark problems and medical classification problems like breast cancer, diabets, liver disorders classification problems. The conducted medical classification task was performed for ECG arrhythmia data taken from UCI repository of machine-learning. Firsly, ECG dataset is normalized in the range of [0,1] and is weighted with fuzzy weighted pre-processing. Then, weighted input values obtained from fuzzy weighted pre-processing is classified by using AIRS classifier system. In this study, fuzzy weighted pre-processing, which can be improved by ours, is a new method and firstly, it is applied to ECG dataset. Classifier system consists of three stages: 50-50% of traing-test dataset, 70-30% of traing-test dataset and 80-20% of traing-test dataset, subsequently, the obtained classification accuries: 78.79, 75.00 and 80.77%.en_US
dc.description.provenanceMade available in DSpace on 2020-03-26T17:02:57Z (GMT). No. of bitstreams: 0 Previous issue date: 2006en
dc.identifier.citationPolat, K., Şahan, S., Güneş, S., (2006). A New Method to Medical Diagnosis: Artificial Immune Recognition System (Airs) With Fuzzy Weighted Pre-Processing and Application to Ecg Arrhythmia. Expert Systems With Applications, (31), 264-269. Doi:10.1016/j.eswa.2005.09.019
dc.identifier.doi10.1016/j.eswa.2005.09.019en_US
dc.identifier.endpage269en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issn1873-6793en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage264en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2005.09.019
dc.identifier.urihttps://hdl.handle.net/20.500.12395/20292
dc.identifier.volume31en_US
dc.identifier.wosWOS:000237645100006en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorPolat, Kemal
dc.institutionauthorGüneş, Salih
dc.language.isoenen_US
dc.publisherPergamon-elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectEcg arrhythmiaen_US
dc.subjectArtificial immune systemen_US
dc.subjectAırsen_US
dc.subjectFuzzy weighted pre-processingen_US
dc.titleA New Method to Medical Diagnosis: Artificial Immune Recognition System (Airs) With Fuzzy Weighted Pre-Processing and Application to Ecg Arrhythmiaen_US
dc.typeArticleen_US

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