The medical applications of attribute weighted artificial immune system (AWAIS): Diagnosis of Heart and Diabetes Diseases

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dc.contributor.authorSahan, S
dc.contributor.authorPolat, K
dc.contributor.authorKodaz, H
dc.contributor.authorGunes, S
dc.date.accessioned2020-03-26T16:58:16Z
dc.date.available2020-03-26T16:58:16Z
dc.date.issued2005
dc.departmentSelçuk Üniversitesien_US
dc.description4th International Conference on Artificial Immune Systems -- AUG 14-17, 2005 -- Banff, CANADAen_US
dc.description.abstractIn our previous work, we had been proposed a new artificial immune system named as Attribute Weighted Artificial Immune System (AWAIS) to eliminate the negative effects of taking into account of all attributes in calculating Euclidean distance in shape-space representation which is used in many network-based Artificial Immune Systems (AISs), This system depends on the weighting attributes with respect to their importance degrees in class discrimination. These weights are then used in calculation of Euclidean distances. The performance analyses were conducted in the previous study by using machine learning benchmark datasets. In this study, the performance of AWAIS was investigated for real world problems. The used datasets were medical datasets consisting of Statlog Heart Disease and Pima Indian Diabetes datasets taken from University of California at Irvine (UCI) Machine Learning Repository. Classification accuracies for these datasets were obtained through using 10-fold cross validation method. AWAIS reached 82.59% classification accuracy for Statlog Heart Disease while it obtained a classification accuracy of 75.87% for Pima Indians Diabetes. These results are comparable with other classifiers and give promising performance to AWAIS for that kind of problems.en_US
dc.description.sponsorshipUniv Calgary, Fac Sci, Univ Calgary, Dept Biochem & Mol biol, Univ Calgary, Dept Comp Sci, ARTIST, iCORE, MITACS, PIMSen_US
dc.identifier.endpage468en_US
dc.identifier.isbn3-540-28175-4
dc.identifier.issn0302-9743en_US
dc.identifier.issn1611-3349en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage456en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/19930
dc.identifier.volume3627en_US
dc.identifier.wosWOS:000231416700035en_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.ispartofARTIFICIAL IMMUNE SYSTEMS, PROCEEDINGSen_US
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleThe medical applications of attribute weighted artificial immune system (AWAIS): Diagnosis of Heart and Diabetes Diseasesen_US
dc.typeConference Objecten_US

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