A deep CNN-based acoustic model for the identification of lung diseases utilizing extracted MFCC features from respiratory sounds
Author:
Funder
Deanship of Scientific Research, Princess Nourah Bint Abdulrahman University
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11042-024-18703-0.pdf
Reference39 articles.
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2. Mashika M, van der Haar D (2023) Mel frequency Cepstral coefficients and Support Vector machines for Cough Detection pp 250–259.https://doi.org/10.1007/978-3-031-35748-0_18
3. Nayak SS, Darji AD, Shah PK (2023) Machine learning approach for detecting Covid-19 from speech signal using Mel frequency magnitude coefficient. Signal Image Video Process 17(6):3155–3162. https://doi.org/10.1007/s11760-023-02537-8
4. Garcia-Mendez JP et al (2023) Machine learning for automated classification of abnormal lung sounds obtained from public databases: a systematic review. Bioengineering 10(10):1155. https://doi.org/10.3390/bioengineering10101155
5. Issahaku FY, Liu X, Lu K, Fang X, Danwana SB, Asimeng E (2024) Multimodal deep learning model for Covid-19 detection. Biomed Signal Process Control 91:105906. https://doi.org/10.1016/j.bspc.2023.105906
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