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

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 suc...

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Bibliographic Details
Published in:Pattern recognition 2006-11, Vol.39 (11), p.2186-2193
Main Authors: Polat, Kemal, Güneş, Salih, Tosun, Sülayman
Format: Article
Language:English
Subjects:
AIRS
Artificial immune system
Fuzzy weighted pre-processing
Heart disease
k-fold cross validation
Medical diagnosis
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Summary: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.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2006.05.028