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 …

The primary objective of this paper is to build classification models and strategies to identify
breathing sound anomalies (wheeze, crackle) for automated diagnosis of respiratory and …

Lung auscultation has long been used as a valuable medical tool to assess respiratory
health and has gotten a lot of attention in recent years, notably following the coronavirus …

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 …

Computerized auscultation of lung sounds is gaining importance today with the availability
of lung sounds and its potential in overcoming the limitations of traditional diagnosis …

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 are among the most common causes of severe illness and death
worldwide. Prevention and early diagnosis are essential to limit or even reverse the trend …

Improving access to health care services for the medically under-served population is vital to
ensure that critical illness can be addressed immediately. In the scenarios where there is a …

This paper presents and explores a robust deep learning framework for auscultation
analysis. This aims to classify anomalies in respiratory cycles and detect diseases, from …