Journal ArticleDOI
Multichannel lung sound analysis for asthma detection.
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TLDR
The proposed multichannel asthma detection method, where the presence of wheeze in lung sound is not a necessary requirement, outperforms commonly used lung sound classification methods in this field and provides significant relative improvement.About:
This article is published in Computer Methods and Programs in Biomedicine.The article was published on 2018-03-09. It has received 43 citations till now.read more
Citations
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Journal ArticleDOI
Detecting Respiratory Pathologies Using Convolutional Neural Networks and Variational Autoencoders for Unbalancing Data.
María Teresa García-Ordás,José Alberto Benítez-Andrades,Isaías García-Rodríguez,Carmen Benavides,Héctor Alaiz-Moretón +4 more
TL;DR: This paper carried out a more challenging classification trying to distinguish between the different types of pathologies or healthy: URTI, COPD, Bronchiectasis, Pneumonia, and Bronchiolitis and achieved results up to 0.990 F-Score in the more challenging six-class classification.
Journal ArticleDOI
Lung Sound Recognition Algorithm Based on VGGish-BiGRU
TL;DR: A lung sound recognition algorithm based on VGGish-BiGRU is proposed on the basis of transfer learning, which combines V GGish network with the bidirectional gated recurrent unit neural network (Bi GRU).
Journal ArticleDOI
Applications of artificial intelligence and machine learning in respiratory medicine
TL;DR: Progress in deep neural networks within respiratory medicine over the past 5 years is surveyed, highlighting the current limitations of AI and machine learning and the potential for future developments.
Journal ArticleDOI
Automatic identification of respiratory diseases from stethoscopic lung sound signals using ensemble classifiers
Luay Fraiwan,Omnia Hassanin,Mohammad Fraiwan,Basheer Khassawneh,Ali M. Ibnian,Mohanad Alkhodari +5 more
TL;DR: The investigated ensemble classification methods exhibited a promising performance for detecting a wide range of respiratory disease conditions and the data fusion approach provides a promising insight into an alternative and more suitable solution to reduce the effect of imbalanced data for clinical applications in general and respiratory sound analysis studies in specific.
Journal ArticleDOI
Characterization and classification of asthmatic wheeze sounds according to severity level using spectral integrated features.
TL;DR: In the classification experiments, the ensemble classifier exhibited better performance in terms of sensitivity, specificity and positive predictive value (PPV), and the trachea inspiratory group showed the highest classification performance compared with all the other groups.
References
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LIBSVM: A library for support vector machines
Chih-Chung Chang,Chih-Jen Lin +1 more
TL;DR: Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.
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Support-Vector Networks
Corinna Cortes,Vladimir Vapnik +1 more
TL;DR: High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.
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The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms
TL;DR: In this article, the use of the fast Fourier transform in power spectrum analysis is described, and the method involves sectioning the record and averaging modified periodograms of the sections.
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On the use of windows for harmonic analysis with the discrete Fourier transform
TL;DR: A comprehensive catalog of data windows along with their significant performance parameters from which the different windows can be compared is included, and an example demonstrates the use and value of windows to resolve closely spaced harmonic signals characterized by large differences in amplitude.