Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database …
FS Hsu, SR Huang, CW Huang, CJ Huang… - PLoS …, 2021 - journals.plos.org
A reliable, remote, and continuous real-time respiratory sound monitor with automated
respiratory sound analysis ability is urgently required in many clinical scenarios—such as in …
respiratory sound analysis ability is urgently required in many clinical scenarios—such as in …
[PDF][PDF] LungRN+ NL: An improved adventitious lung sound classification using non-local block resnet neural network with mixup data augmentation.
Y Ma, X Xu, Y Li - Interspeech, 2020 - interspeech2020.org
Performing an automated adventitious lung sound detection is a challenging task since the
sound is susceptible to noises (heartbeat, motion artifacts, and audio sound) and there is …
sound is susceptible to noises (heartbeat, motion artifacts, and audio sound) and there is …
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 …
Classify respiratory abnormality in lung sounds using stft and a fine-tuned resnet18 network
Recognizing patterns in lung sounds is crucial to detecting and monitoring respiratory
diseases. Current techniques for analyzing respiratory sounds demand domain experts and …
diseases. Current techniques for analyzing respiratory sounds demand domain experts and …
Automated lung sound classification using a hybrid CNN-LSTM network and focal loss function
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 …
affect the patient's quality of life. Early diagnosis and patient monitoring, which …
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 …
Abnormal respiratory sounds classification using deep CNN through artificial noise addition
Respiratory sound (RS) attributes and their analyses structure a fundamental piece of
pneumonic pathology, and it gives symptomatic data regarding a patient's lung. A couple of …
pneumonic pathology, and it gives symptomatic data regarding a patient's lung. A couple of …
Arsc-net: Adventitious respiratory sound classification network using parallel paths with channel-spatial attention
Automatic identification of adventitious respiratory sound has still been a challenging
problem in recent years. To address this challenge, we propose an adventitious respiratory …
problem in recent years. To address this challenge, we propose an adventitious respiratory …
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 …
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 …