An edge-device-compatible algorithm for valvular heart diseases screening using phonocardiogram signals with a lightweight convolutional neural network and self-supervised learning
Published 2023 View Full Article
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Title
An edge-device-compatible algorithm for valvular heart diseases screening using phonocardiogram signals with a lightweight convolutional neural network and self-supervised learning
Authors
Keywords
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Journal
Computer Methods and Programs in Biomedicine
Volume -, Issue -, Pages 107906
Publisher
Elsevier BV
Online
2023-11-05
DOI
10.1016/j.cmpb.2023.107906
References
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- (2020) Neeraj Baghel et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Phonocardiogram signals processing approach for PASCAL Classifying Heart Sounds Challenge
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- (2018) Kim-Han Thung et al. MULTIMEDIA TOOLS AND APPLICATIONS
- Classification of Heart Sound Signal Using Multiple Features
- (2018) Yaseen et al. Applied Sciences-Basel
- Characterization of $S_1$ and $S_2$ Heart Sounds Using Stacked Autoencoder and Convolutional Neural Network
- (2018) Madhusudhan Mishra et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
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- An open access database for the evaluation of heart sound algorithms
- (2016) Chengyu Liu et al. PHYSIOLOGICAL MEASUREMENT
- Separation of Heart Sound Signal from Noise in Joint Cycle Frequency–Time–Frequency Domains Based on Fuzzy Detection
- (2010) Hong Tang et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Segmentation of heart sound recordings by a duration-dependent hidden Markov model
- (2010) S E Schmidt et al. PHYSIOLOGICAL MEASUREMENT
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