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

Abstract Machine learning has proven to be an effective technique in recent years and
machine learning algorithms have been successfully used in a large number of applications …

In the field of medicine, with the introduction of computer systems that can collect and
analyze massive amounts of data, many non-invasive diagnostic methods are being …

Lung sounds convey useful information related to pulmonary pathology. In this paper, short-
term spectral characteristics of lung sounds are studied to characterize the lung sounds for …

Pulmonary breathing sound plays a key role in the prevention and diagnosis of the lung
diseases. Its correlation with pathology and physiology has become an important research …

In this paper, we present an approach for multi-channel lung sound classification, exploiting
spectral, temporal and spatial information. In particular, we propose a frame-wise …

Abstract Background: The World Health Organization (WHO) establishes as a top priority the
early detection of respiratory diseases. This detection could be performed by means of …

Background and objective Lung sound signals convey valuable information of the lung
status. Auscultation is an effective technique to appreciate the condition of the respiratory …

This paper proposed various feature extraction procedures to separate crackles and rhonchi
of pathological lung sounds from normal lung sounds. The feature extraction process for …

Heart failure (HF) exacerbations, characterized by pulmonary congestion and
breathlessness, require frequent hospitalizations, often resulting in poor outcomes. Current …