This study proposes an accurate asthma detection model using an attention network and
machine learning technique. The objective of this study is the automated detection of asthma …

This review delves into the burgeoning field of explainable artificial intelligence (XAI) in the
detection and analysis of lung diseases through vocal biomarkers. Lung diseases, often …

COPD is a progressive disease that may lead to death if not diagnosed and treated at an
early stage. The examination of vital signs such as respiration rate is a promising approach …

The use of machine learning in biomedical research has surged in recent years thanks to
advances in devices and artificial intelligence. Our aim is to expand this body of knowledge …

Chronic obstructive pulmonary disease (COPD) is a complex and multi-component
respiratory disease. Computed tomography (CT) images can characterize lesions in COPD …

Sound classification has obtained considerable attention in recent years due to its wide
range of applications in various fields, such as speech recognition, sound surveillance …

Asthma is a common disease. The clinical diagnosis is usually confirmed on a pulmonary
function test, which is not always readily accessible. We aimed to develop a computationally …

Abstract Characterization of lung sounds (LS) is indispensable for diagnosing respiratory
pathology. Although conventional neural networks (NNs) have been widely employed for the …

The study presents a computer-based automated system that employs machine learning to
classify pulmonary diseases using lung sound data collected from hospitals. Denoising …

Respiratory sounds heard through the stethoscope lend useful information for diagnostic
purposes. However, the accuracy and efficiency of clinical diagnosis are constrained by …