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For: Pahar M, Klopper M, Warren R, Niesler T. COVID-19 detection in cough, breath and speech using deep transfer learning and bottleneck features. Comput Biol Med 2021;141:105153. [PMID: 34954610 DOI: 10.1016/j.compbiomed.2021.105153] [Cited by in Crossref: 10] [Cited by in F6Publishing: 2] [Article Influence: 10.0] [Reference Citation Analysis]
Number Citing Articles
1 Sharma G, Umapathy K, Krishnan S. Audio texture analysis of COVID-19 cough, breath, and speech sounds. Biomedical Signal Processing and Control 2022;76:103703. [DOI: 10.1016/j.bspc.2022.103703] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
2 Heidari A, Jafari Navimipour N, Unal M, Toumaj S. Machine learning applications for COVID-19 outbreak management. Neural Comput Appl 2022;:1-36. [PMID: 35702664 DOI: 10.1007/s00521-022-07424-w] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
3 Chen Z, Li M, Wang R, Sun W, Liu J, Li H, Wang T, Lian Y, Zhang J, Wang X. Diagnosis of COVID-19 via Acoustic Analysis and Artificial Intelligence by Monitoring Breath Sounds on Smartphones. J Biomed Inform 2022;:104078. [PMID: 35489595 DOI: 10.1016/j.jbi.2022.104078] [Reference Citation Analysis]
4 Haq IU, Du X, Jan H. Implementation of smart social distancing for COVID-19 based on deep learning algorithm. Multimed Tools Appl. [DOI: 10.1007/s11042-022-13154-x] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Han J, Xia T, Spathis D, Bondareva E, Brown C, Chauhan J, Dang T, Grammenos A, Hasthanasombat A, Floto A, Cicuta P, Mascolo C. Sounds of COVID-19: exploring realistic performance of audio-based digital testing. NPJ Digit Med 2022;5:16. [PMID: 35091662 DOI: 10.1038/s41746-021-00553-x] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 5.0] [Reference Citation Analysis]