A hybrid automated detection system based on least square support vector machine classifier and k-NN based weighted pre-processing for diagnosing of macular disease
Küçük Resim Yok
Tarih
2007
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SPRINGER-VERLAG BERLIN
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this paper, we proposed a hybrid automated detection system based least square support vector machine (LSSVM) and k-NN based weighted pre-processing for diagnosing of macular disease from the pattern electroretinography (PERG) signals. k-NN based weighted pre-processing is pre-processing method, which is firstly proposed by us. The proposed system consists of two parts: k-NN based weighted pre-processing used to weight the PERG signals and LSSVM classifier used to distinguish between healthy eye and diseased eye (macula diseases). The performance and efficiency of proposed system was conducted using classification accuracy and 10-fold cross validation. The results confirmed that a hybrid automated detection system based on the LSSVM and k-NN based weighted pre-processing has potential in detecting macular disease. The stated results show that proposed method could point out the ability of design of a new intelligent assistance diagnosis system.
Açıklama
8th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA) -- APR 11-14, 2007 -- Warsaw Univ Technol, Warsaw, POLAND
Anahtar Kelimeler
Kaynak
ADAPTIVE AND NATURAL COMPUTING ALGORITHMS, PT 2
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
4432
