Deep learning based respiratory sound analysis for detection of chronic obstructive pulmonary disease
A Srivastava, S Jain, R Miranda, S Patil… - PeerJ Computer …, 2021 - peerj.com
In recent times, technologies such as machine learning and deep learning have played a
vital role in providing assistive solutions to a medical domain's challenges. They also …
vital role in providing assistive solutions to a medical domain's challenges. They also …
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 …
Inception-based network and multi-spectrogram ensemble applied to predict respiratory anomalies and lung diseases
This paper presents an inception-based deep neural network for detecting lung diseases
using respiratory sound input. Recordings of respiratory sound collected from patients are …
using respiratory sound input. Recordings of respiratory sound collected from patients are …
Convolutional neural network-based model for lung sounds classification
Deep learning approaches are gaining popularity in the medical field for diagnostics and
predictive analytics. This study aims to improve the classification of respiratory sounds …
predictive analytics. This study aims to improve the classification of respiratory sounds …
Crackle detection in lung sounds using transfer learning and multi-input convolutional neural networks
T Nguyen, F Pernkopf - … Conference of the IEEE Engineering in …, 2021 - ieeexplore.ieee.org
Large annotated lung sound databases are publicly available and might be used to train
algorithms for diagnosis systems. However, it might be a challenge to develop a well …
algorithms for diagnosis systems. However, it might be a challenge to develop a well …
Lung sounds classification using wavelet reconstructed sub-bands signal and machine learning
The incidence of respiratory diseases is increasing rapidly due to environmental pollution
affecting everyone around the world. Diagnosis from cardiopulmonary hearing has been …
affecting everyone around the world. Diagnosis from cardiopulmonary hearing has been …
Multi-path Convolutional Neural Networks Efficiently Improve Feature Extraction in Continuous Adventitious Lung Sound Detection
FS Hsu, SR Huang, CW Huang, CC Chen… - arXiv preprint arXiv …, 2021 - arxiv.org
We previously established a large lung sound database, HF_Lung_V2 (Lung_V2). We
trained convolutional-bidirectional gated recurrent unit (CNN-BiGRU) networks for detecting …
trained convolutional-bidirectional gated recurrent unit (CNN-BiGRU) networks for detecting …
Classification of respiration sounds using deep pre-trained audio embeddings
CAG Meza, JA del Hoyo Ontiveros… - 2021 IEEE Latin …, 2021 - ieeexplore.ieee.org
In this work we present the use of an end-to-end deep learning based pre-trained audio
embeddings generator, and apply it to the purpose of classification of respiration sounds …
embeddings generator, and apply it to the purpose of classification of respiration sounds …
[图书][B] Robust deep learning frameworks for acoustic scene and respiratory sound classification
LD Pham - 2021 - search.proquest.com
Abstract Although research on Acoustic Scene Classification (ASC) is very close to, or even
overshadowed by different popular research areas known as Automatic Speech Recognition …
overshadowed by different popular research areas known as Automatic Speech Recognition …
Support vector machine-based diagnosis of Tuberculosis
M Shakeel, Z Mushtaq, P Gretschmann… - 2021 Mohammad Ali …, 2021 - ieeexplore.ieee.org
Tuberculosis is one of the common death-causing diseases in the world and possess a
threat to the health of the world population. This study aims to elaborate on the feasibility of …
threat to the health of the world population. This study aims to elaborate on the feasibility of …