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

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 …

In recent times, technologies such as machine learning and deep learning have played a
vital role in providing assistive solutions to a medical domain's challenges. They also …

Death rate associated with respiratory diseases is a global concern. The various challenges
incorporated in respiratory health management are due to delayed and inaccurate …

Listening to lung sounds through auscultation is vital in examining the respiratory system for
abnormalities. Automated analysis of lung auscultation sounds can be beneficial to the …

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 …

Monitoring of prevalent airborne diseases such as COVID-19 characteristically involves
respiratory assessments. While auscultation is a mainstream method for preliminary …

Auscultation, or listening to body sounds with a stethoscope, is the most basic and
instructive part of the physical examination. Although it is a quick and effective way of …

This paper evaluates a range of deep learning frameworks for detecting respiratory
anomalies from input audio. Audio recordings of respiratory cycles collected from patients …