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COVID-19 Disease Progression Prediction via Audio Signals: A Longitudinal Study. (arXiv:2201.01232v1 [cs.SD])
Jan. 5, 2022, 2:10 a.m. | Ting Dang, Jing Han, Tong Xia, Dimitris Spathis, Erika Bondareva, Chloë Brown, Jagmohan Chauhan, Andreas Grammenos, Apinan Hasthanasombat, Andres
cs.LG updates on arXiv.org arxiv.org
Recent work has shown the potential of the use of audio data in screening for
COVID-19. However, very little exploration has been done of monitoring disease
progression, especially recovery in COVID-19 through audio. Tracking disease
progression characteristics and patterns of recovery could lead to tremendous
insights and more timely treatment or treatment adjustment, as well as better
resources management in health care systems.
The primary objective of this study is to explore the potential of
longitudinal audio dynamics for COVID-19 …
More from arxiv.org / cs.LG updates on arXiv.org
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