Machine learning for detecting COVID-19 from cough sounds: An ensemble-based MCDM method
Author:
Publisher
Elsevier BV
Subject
Health Informatics,Computer Science Applications
Reference56 articles.
1. M. Salath, C. L. Althaus, R. Neher, S. Stringhini, E. Hodcroft, J. Fellay, M. Zwahlen, G. Senti, M. Battegay, A. Wilder-Smith, E. Isabella, E. Matthias, L. Nicola, COVID-19 epidemic in Switzerland: on the importance of testing, contact tracing and isolation, Swiss Med. Wkly..doi:10.4414/smw.2020.20225.
2. AI4COVID-19: AI enabled preliminary diagnosis for COVID-19 from cough samples via an app;Imran;Inf. Med. Unlocked,2020
3. L. Wang, Z. Q. Lin, A. Wong, COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images, Sci. Rep. 10 (1). doi:10.1038/s41598-020-76550-z.
4. N. K. Chowdhury, R. Md. Muhtadir, M. A. Kabir, PDCOVIDNet: a parallel-dilated convolutional neural network architecture for detecting COVID-19 from chest X-ray images, Health Inf. Sci. Syst. 8 (27). doi:10.1007/s13755-020-00119-3.
5. N. K. Chowdhury, M. A. Kabir, M. M. Rahman, N. Rezoana, ECOVNet: a highly effective ensemble based deep learning model for detecting COVID-19, PeerJ Comput. Sci. 7. doi:10.7717/peerj-cs.551.
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