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

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Küçük Resim

Tarih

2006

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Elsevier Sci Ltd

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

Artificial 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.

Açıklama

Anahtar Kelimeler

Fuzzy resource allocation, AIRS, Lymph diseases, k-Fold cross-validation, Expert system

Kaynak

Biomedical Signal Processing and Control

WoS Q Değeri

N/A

Scopus Q Değeri

Q1

Cilt

1

Sayı

Künye

Güneş, 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