Abstract Background and Objective: Respiratory diseases are among the most significant
causes of morbidity and mortality worldwide, causing substantial strain on society and health …

Respiratory diseases represent a significant global burden, necessitating efficient diagnostic
methods for timely intervention. Digital biomarkers based on audio, acoustics, and sound …

Methods based on supervised learning using annotations in an end-to-end fashion have
been the state-of-the-art for classification problems. However, they may be limited in their …

Automated respiratory sound classification aims to provide a rapid and reliable diagnosis of
respiratory disease. However, the database used to develop a lung sounds classification …

Globally, respiratory diseases are the leading cause of death, making it essential to develop
an automatic respiratory sounds software to speed up diagnosis and reduce physician …

Accurate analysis and classification of respiratory sound play an important role in the
diagnosis of respiratory diseases. Most of the current methods for classifying respiratory …

Respiratory diseases have seriously impacted human life in the last couple of years; as
Covid 19 arrived, many lost their beloved ones. Since respiratory diseases directly attack the …

Patients with respiratory conditions typically exhibit adventitious respiratory sounds (ARS),
such as wheezes and crackles. In recent years, computerized methods for analyzing …

The field of medical acoustics is gaining constantly-increasing attention by the scientific
community, with the the general goal being the automatic understanding of medical related …

This paper presents a deep learning system applied for detecting anomalies from respiratory
sound recordings. Our system initially performs audio feature extraction using Continuous …