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A new diagnosis method for heart valve disease by Using Antibody Memory Clone Clustering Algorithm based on Supervised Gath-Geva algorithm
2010
2010 3rd International Conference on Computer Science and Information Technology
In order to discriminate normal and abnormal heart sounds (HSs) accurately and effectively, a new method for clinical diagnosis of the heart valve diseases is proposed. The method is composed of three stages. The first stage is the preprocessing stage. During the pre-processing stage, the improved wavelet threshold shrinkage denoising algorithm is used for the noise reduction of the measured HSs. In the feature extraction stage, the normalized average Shannon energy theorem and wavelet
doi:10.1109/iccsit.2010.5563722
fatcat:gpgfia7r7jfrfleuws6yv34chy