Lungbrn: A smart digital stethoscope for detecting respiratory disease using bi-resnet deep learning algorithm
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 …
ensure that critical illness can be addressed immediately. In the scenarios where there is a …
Respirenet: A deep neural network for accurately detecting abnormal lung sounds in limited data setting
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 …
diseases. Automated analysis, coupled with digital stethoscopes, can play a crucial role in …
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 …
RDLINet: A novel lightweight inception network for respiratory disease classification using lung sounds
Respiratory diseases are the world's third leading cause of mortality. Early detection is
critical in dealing with respiratory diseases, as it improves the effectiveness of intervention …
critical in dealing with respiratory diseases, as it improves the effectiveness of intervention …
Classification of lung sounds with CNN model using parallel pooling structure
The recognition of various lung sounds recorded using electronic stethoscopes plays a
significant role in the early diagnoses of respiratory diseases. To increase the accuracy of …
significant role in the early diagnoses of respiratory diseases. To increase the accuracy of …
LungAttn: advanced lung sound classification using attention mechanism with dual TQWT and triple STFT spectrogram
J Li, J Yuan, H Wang, S Liu, Q Guo, Y Ma… - Physiological …, 2021 - iopscience.iop.org
Objective. Auscultation of lung sound plays an important role in the early diagnosis of lung
diseases. This work aims to develop an automated adventitious lung sound detection …
diseases. This work aims to develop an automated adventitious lung sound detection …
[HTML][HTML] Respiratory sound classification for crackles, wheezes, and rhonchi in the clinical field using deep learning
Auscultation has been essential part of the physical examination; this is non-invasive, real-
time, and very informative. Detection of abnormal respiratory sounds with a stethoscope is …
time, and very informative. Detection of abnormal respiratory sounds with a stethoscope is …
Efficiently classifying lung sounds through depthwise separable CNN models with fused STFT and MFCC features
Lung sounds remain vital in clinical diagnosis as they reveal associations with pulmonary
pathologies. With COVID-19 spreading across the world, it has become more pressing for …
pathologies. With COVID-19 spreading across the world, it has become more pressing for …
Lung sound classification using snapshot ensemble of convolutional neural networks
T Nguyen, F Pernkopf - … Conference of the IEEE Engineering in …, 2020 - ieeexplore.ieee.org
We propose a robust and efficient lung sound classification system using a snapshot
ensemble of convolutional neural networks (CNNs). A robust CNN architecture is used to …
ensemble of convolutional neural networks (CNNs). A robust CNN architecture is used to …
Lung disease classification using deep convolutional neural network
The advanced technologies are essential to achieving the improvement of medicine. More
specifically, an extensive investigation in a partnership among researchers, health care …
specifically, an extensive investigation in a partnership among researchers, health care …