Diagnosis of Heart Disease Using Artificial Immune Recognition System and Fuzzy Weighted Pre-Processing
Yükleniyor...
Dosyalar
Tarih
2006
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pergamon-Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This paper presents a novel method for diagnosis of heart disease. The proposed method is based on a hybrid method that uses fuzzy weighted pre-processing and artificial immune recognition system (AIRS). Artificial immune recognition system has showed an effective performance on several problems such as machine learning benchmark problems and medical classification problems like breast cancer, diabetes, liver disorders classification. The robustness of the proposed method is examined using classification accuracy, k-fold cross-validation method and confusion matrix. The obtained classification accuracy is 96.30% and it is very promising compared to the previously reported classification techniques.
Açıklama
Anahtar Kelimeler
heart disease, artificial immune system, AIRS, Fuzzy weighted pre-processing, k-fold cross validation, medical diagnosis
Kaynak
Pattern Recognition
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
39
Sayı
Künye
Polat, K., Güneş, S., Tosun, S., (2006). Diagnosis of Heart Disease Using Artificial Immune Recognition System and Fuzzy Weighted Pre-Processing. Pattern Recognition, (39), 2186-2193. Doi: 10.1016/j.patcog.2006.05.028
