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We present a novel machine learning-based method for heart sound classification which we submitted to the PhysioNet/CinC Challenge 2016. Our method relies on a robust feature representation — generated by a wavelet-based deep convolutional neural network (CNN) — of each cardiac cycle in the test recording, and support vector machine classification. In addition to the CNN-based features, our method...