The coming era of a new auscultation system for analyzing respiratory sounds
Y Kim, YK Hyon, S Lee, SD Woo, T Ha… - BMC Pulmonary …, 2022 - Springer
Auscultation with stethoscope has been an essential tool for diagnosing the patients with
respiratory disease. Although auscultation is non-invasive, rapid, and inexpensive, it has …
respiratory disease. Although auscultation is non-invasive, rapid, and inexpensive, it has …
Deep learning-based lung sound analysis for intelligent stethoscope
Auscultation is crucial for the diagnosis of respiratory system diseases. However, traditional
stethoscopes have inherent limitations, such as inter-listener variability and subjectivity, and …
stethoscopes have inherent limitations, such as inter-listener variability and subjectivity, and …
Sprsound: Open-source sjtu paediatric respiratory sound database
Q Zhang, J Zhang, J Yuan, H Huang… - … Circuits and Systems, 2022 - ieeexplore.ieee.org
It has proved that the auscultation of respiratory sound has advantage in early respiratory
diagnosis. Various methods have been raised to perform automatic respiratory sound …
diagnosis. Various methods have been raised to perform automatic respiratory sound …
Exploring machine learning for audio-based respiratory condition screening: A concise review of databases, methods, and open issues
Auscultation plays an important role in the clinic, and the research community has been
exploring machine learning (ML) to enable remote and automatic auscultation for respiratory …
exploring machine learning (ML) to enable remote and automatic auscultation for respiratory …
Acoustic-based deep learning architectures for lung disease diagnosis: A comprehensive overview
AH Sfayyih, AH Sabry, SM Jameel, N Sulaiman… - Diagnostics, 2023 - mdpi.com
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 …
health and has gotten a lot of attention in recent years, notably following the coronavirus …
A machine learning approach to the development and prospective evaluation of a pediatric lung sound classification model
Auscultation, a cost-effective and non-invasive part of physical examination, is essential to
diagnose pediatric respiratory disorders. Electronic stethoscopes allow transmission …
diagnose pediatric respiratory disorders. Electronic stethoscopes allow transmission …
Lightweight skip connections with efficient feature stacking for respiratory sound classification
Y Choi, H Choi, H Lee, S Lee, H Lee - Ieee Access, 2022 - ieeexplore.ieee.org
As the number of deaths from respiratory diseases due to COVID-19 and infectious diseases
increases, early diagnosis is necessary. In general, the diagnosis of diseases is based on …
increases, early diagnosis is necessary. In general, the diagnosis of diseases is based on …
Robust and interpretable temporal convolution network for event detection in lung sound recordings
Objective: This paper proposes a novel framework for lung sound event detection,
segmenting continuous lung sound recordings into discrete events and performing …
segmenting continuous lung sound recordings into discrete events and performing …
Exploring classical machine learning for identification of pathological lung auscultations
H Razvadauskas, E Vaičiukynas, K Buškus… - Computers in Biology …, 2024 - Elsevier
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 …
advances in devices and artificial intelligence. Our aim is to expand this body of knowledge …
A review on lung disease recognition by acoustic signal analysis with deep learning networks
AH Sfayyih, N Sulaiman, AH Sabry - Journal of big Data, 2023 - Springer
Recently, assistive explanations for difficulties in the health check area have been made
viable thanks in considerable portion to technologies like deep learning and machine …
viable thanks in considerable portion to technologies like deep learning and machine …