Automated Identification of Diseases Related to Lymph System From Lymphography Data Using Artificial Immune Recognition System With Fuzzy Resource Allocation Mechanism (Fuzzy-Airs)

Basit Öğe Kaydı
dc.contributor.authorPolat, Kemal
dc.contributor.authorGüneş, Salih
dc.date.accessioned2020-03-26T17:03:06Z
dc.date.available2020-03-26T17:03:06Z
dc.date.issued2006
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractArtificial immune recognition system (AIRS) classification algorithm, which has an important place among classification algorithms in the field of artificial immune systems, has showed an effective and intriguing performance oil the problems it was applied. AIRS was previously applied to some medical classification problems including breast cancer, Cleveland heart disease, diabetes and it obtained very satisfactory results. So, AIRS proved to be,in efficient artificial intelligence technique in medical field. In this study, the resource allocation mechanism of AIRS was changed with a new one determined by fuzzy-logic. This system, named as fuzzy-AIRS was used as a classifier in the diagnosis of lymph diseases, which is of great importance in medicine. The classifications of lymph diseases dataset taken from University of California at Irvine (UCI) Machine Learning Repository were done using 10-fold cross-validation method. Reached classification accuracies were evaluated by comparing them with reported classifiers in UCI web site in addition to other systems that are applied to the related problems. Also, the obtained classification performances were compared with AIRS with regard to the classification accuracy, number of resources and classification time. While only AIRS algorithm obtained 83.138% classification accuracy, fuzzy-AIRS classified the lymph diseases dataset with 90.00% accuracy. For lymph diseases dataset, fuzzy-AIRS obtained the highest classification accuracy according to the UCI web site, Beside of this success, fuzzy-AIRS gained an important advantage over the AIRS by means of classification time. By reducing classification time as well as obtaining high classification accuracies in the applied datasets, fuzzy-AIRS classifier proved that it could be used as an effective classifier for medical problems.en_US
dc.description.sponsorshipScientific Research Projects of Selcuk UniversitySelcuk University [05401069]en_US
dc.description.sponsorshipThis study is supported by the Scientific Research Projects of Selcuk University (project no. 05401069).en_US
dc.identifier.citationGüneş, S., Polat, K., (2006). Automated Identification of Diseases Related to Lymph System From Lymphography Data Using Artificial Immune Recognition System With Fuzzy Resource Allocation Mechanism (Fuzzy-Airs). Biomedical Signal Processing and Control, (1), 253-260. Doi: 10.1016/j.bspc.2006.11.001
dc.identifier.doi10.1016/j.bspc.2006.11.001en_US
dc.identifier.endpage260en_US
dc.identifier.issn1746-8094en_US
dc.identifier.issn1746-8108en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage253en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.bspc.2006.11.001
dc.identifier.urihttps://hdl.handle.net/20.500.12395/20348
dc.identifier.volume1en_US
dc.identifier.wosWOS:000206466500001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorGüneş, Salih
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofBiomedical Signal Processing and Controlen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectFuzzy resource allocationen_US
dc.subjectAIRSen_US
dc.subjectLymph diseasesen_US
dc.subjectk-Fold cross-validationen_US
dc.subjectExpert systemen_US
dc.titleAutomated Identification of Diseases Related to Lymph System From Lymphography Data Using Artificial Immune Recognition System With Fuzzy Resource Allocation Mechanism (Fuzzy-Airs)en_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
20348.pdf
Boyut:
318.42 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Makale Dosyası
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Elektirik ve Elektronik Mühendisliği/Makale Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu