This research explores a new approach in using deep learning neural network for heart
sound classification. The Michigan heart sound and murmur database (MHSDB) provided by …

Featured Application Combining of multi-features extracted manually and convolutional
neural network classifier for automatic heart sounds classification. Abstract Heart sounds …

This paper presents an automatic normal and abnormal heart sound classification model
developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained …

The mortality rate of heart disease continues to rise each year: developing mechanisms to
reduce mortality from heart disease is a top concern in today's society. Heart sound …

In this study, two models for classifying heart rate sounds are proposed to classify heart
sound by deep learning techniques based on the log-mel spectrogram of heart sound …

This paper presents a fast and cost-effective method for diagnosing cardiac abnormalities
with high accuracy and reliability using low-cost systems in clinics. The primary limitation of …

Background and objective Heart sound contains various important quantities that help early
detection of heart diseases. Many methods have been proposed so far where various signal …

Heart problems have become one of the prevalent impacts on human health. Heart sound
identification techniques play an essential role in predicting heart attacks as a non-invasive …

Heart sound (HS) signals contain valuable diagnostic information for detection of heart
abnormalities. The early detection of heart abnormalities plays an important role in reducing …

In this paper, we present a new method to categorize the heart sound signals into Normal,
Murmur, Extra Heart Sound and Artifact with Convolutional Neural Network (CNN) model …