Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm
Genetic Programming and Evolvable Machines
A decision support system based on support vector machines for diagnosis of the heart valve diseases
Computers in Biology and Medicine
A biomedical system based on hidden Markov model for diagnosis of the heart valve diseases
Pattern Recognition Letters
Computers in Biology and Medicine
Entropy-based algorithms for best basis selection
IEEE Transactions on Information Theory - Part 2
Diagnosis of valvular heart disease through neural networks ensembles
Computer Methods and Programs in Biomedicine
Evaluation of ensemble methods for diagnosing of valvular heart disease
Expert Systems with Applications: An International Journal
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The use of artificial intelligence methods in medical analysis is increasing. This is mainly because the effectiveness of classification and detection systems has improved in a great deal to help medical experts in diagnosing. In this paper, we investigate the performance of an artificial immune system (AIS) based fuzzy k-NN algorithm to determine the heart valve disorders from the Doppler heart sounds. The proposed methodology is composed of three stages. The first stage is the pre-processing stage. The feature extraction is the second stage. During feature extraction stage, Wavelet transforms and short time Fourier transform were used. As next step, wavelet entropy was applied to these features. In the classification stage, AIS based fuzzy k-NN algorithm is used. To compute the correct classification rate of proposed methodology, a comparative study is realized by using a data set containing 215 samples. The validation of the proposed method is measured by using the sensitivity and specificity parameters. 95.9% sensitivity and 96% specificity rate was obtained.