Extraction and assessment of diagnosis-relevant features for heart murmur classification

•Novel features were devised and extracted from clinical heart sound data.•The feature set was refined using an information gain approach.•Murmurs were classified with k-nearest neighbor and support vector machine algorithms.•The feature set resulted in a classification accuracy consistently above 90%.