Abstract The integration of Deep Learning (DL) and the Internet of Things (IoT) has
revolutionized technology in the twenty-first century, enabling humans and machines to …

Auscultation is crucial for the diagnosis of respiratory system diseases. However, traditional
stethoscopes have inherent limitations, such as inter-listener variability and subjectivity, and …

Respiratory diseases constitute one of the leading causes of death worldwide and directly
affect the patient's quality of life. Early diagnosis and patient monitoring, which …

Computer-aided detection using Deep Learning (DL) and Machine Learning (ML) shows
tremendous growth in the medical field. Medical images are considered as the actual origin …

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 …

Auscultation of respiratory sounds is the primary tool for screening and diagnosing lung
diseases. Automated analysis, coupled with digital stethoscopes, can play a crucial role in …

Respiratory diseases have been increasingly affecting people worldwide, posing a major
public health challenge due to rising morbidity and mortality rates. Subtle abnormal …

Performing an automated adventitious lung sound detection is a challenging task since the
sound is susceptible to noises (heartbeat, motion artifacts, and audio sound) and there is …

Stethoscopes were originally designed for the auscultation of a patient's chest for the
purpose of listening to lung and heart sounds. These aid medical professionals in their …

A reliable, remote, and continuous real-time respiratory sound monitor with automated
respiratory sound analysis ability is urgently required in many clinical scenarios—such as in …