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Classification of normal and abnormal lung sounds using neural network and support vector machines
2013
2013 21st Iranian Conference on Electrical Engineering (ICEE)
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This work proposes feature extraction of lung sounds using wavelet coefficients and their classification by neural network and support vector machines. The lung sounds were classified into 6 classes. The results stated the advantages of a support vector machines for the classification of normal and abnormal lung sounds, and indicated that SVMs are a highly successful classifier with accuracy about 93.51 -100 for classification of lung sounds.
doi:10.1109/iraniancee.2013.6599555
fatcat:jzkigkyiaffn7pbcv7x5fyz3lq