Computer aided medical diagnosis system based on principal component analysis and artificial immune recognition system classifier algorithm
Küçük Resim Yok
Tarih
2008
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
PERGAMON-ELSEVIER SCIENCE LTD
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, diagnosis of lung cancer, which is a very common and important disease, was conducted with computer aided medical diagnosis system based on principal component analysis and artificial immune recognition system. The approach system has two stages. In the first stage, dimension of lung cancer dataset that has 57 features is reduced to 4 features using principal component analysis. In the second stage, artificial immune recognition system (AIRS) was our used classifier. We took the lung cancer dataset used in our study from the UCI (from University of California, Department of Information and Computer Science) Machine Learning Database. The obtained classification accuracy of our system was 100% and it was very promising with regard to the other classification applications in literature for this problem. (c) 2006 Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
lung cancer, principal component analysis (PCA), artificial immune system, AIRS, medical diagnosis
Kaynak
EXPERT SYSTEMS WITH APPLICATIONS
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
34
Sayı
1
