Diagnosis of heart disease using artificial immune recognition system and fuzzy weighted pre-processing

被引:52
|
作者
Polat, Kemal [1 ]
Gunes, Salih
Tosun, Sulayman
机构
[1] Selcuk Univ, Elect & Elect Engn, Konya 42035, Turkey
[2] Selcuk Univ, Comp Engn Dept, TR-42035 Konya, Turkey
关键词
heart disease; artificial immune system; AIRS; Fuzzy weighted pre-processing; k-fold cross validation; medical diagnosis;
D O I
10.1016/j.patcog.2006.05.028
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:2186 / 2193
页数:8
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