Feature extraction and representation has significant impact on the performance of any
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …

The automated classification of heart sounds plays a significant role in the diagnosis of
cardiovascular diseases (CVDs). With the recent introduction of medical big data and …

As cardiovascular disorders are prevalent, there is a growing demand for reliable and
precise diagnostic methods within this domain. Audio signal-based heart disease detection …

In view of the important role of heart sound signals in diagnosing and preventing congenital
heart disease, a novel method about feature extraction and classification of heart sound …

Cardiovascular diseases have become one of the most prevalent threats to human health
throughout the world. As a noninvasive assistant diagnostic tool, the heart sound detection …

Heart-sound auscultation is one of the most widely used approaches for detecting
cardiovascular disorders. Diagnosing abnormalities of heart sound using a stethoscope …

Cardiovascular diseases (CVD) are the most widely spread diseases all over the world
among the common chronic diseases. CVD represents one of the main causes of morbidity …

Automatic classification of heart sound plays an important role in the diagnosis of
cardiovascular diseases. In this study, a heart sound sample classification method based on …

Heart sound classification plays a critical role in the early diagnosis of cardiovascular
diseases. Although there have been many advances in heart sound classification in the last …

Phonocardiogram (PCG) signals reflect the mechanical activity of the heart. Previous studies
have reported that PCG signals contain heart murmurs caused by coronary artery disease …