Computational methods for lung sound analysis are beneficial for computer-aided diagnosis
support, storage and monitoring in critical care. In this paper, we use pre-trained ResNet …

Pulmonary auscultation is essential for detecting abnormal lung sounds during physical
assessments, but its reliability depends on the operator. Machine learning (ML) models offer …

The use of computer-based automated approaches and improvements in lung sound
recording techniques have made lung sound-based diagnostics even better and devoid of …

Respiratory sound contains crucial information for the early diagnosis of fatal lung diseases.
Since the COVID-19 pandemic, there has been a growing interest in contact-free medical …

As the number of deaths from respiratory diseases due to COVID-19 and infectious diseases
increases, early diagnosis is necessary. In general, the diagnosis of diseases is based on …

Discrimination of normal and adventitious respiratory sounds from stethoscope auscultation
by human ears is challenging owing to low frequency characteristics and varying frequency …

Passive recognition of ship-radiated noise plays a crucial role in military and economic
domains. However, underwater environments pose significant challenges due to inherent …

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 …