Sounds of COVID-19: exploring realistic performance of audio-based digital testing

Sounds of COVID-19: exploring realistic performance of audio-based digital testing

Abstract To identify Coronavirus disease (COVID-19) cases efficiently, affordably, and at scale, recent work has shown how audio (including cough, breathing and voice) based approaches can be used for testing. However, there is a lack of exploration of how biases and methodological decisions impact...

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Bibliographic Details
Main Authors: Jing Han, Tong Xia, Dimitris Spathis, Erika Bondareva, Chloë Brown, Jagmohan Chauhan, Ting Dang, Andreas Grammenos, Apinan Hasthanasombat, Andres Floto, Pietro Cicuta, Cecilia Mascolo
Format: Article
Language:English
Published: Nature Portfolio 2022-01-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-021-00553-x

Internet

https://doi.org/10.1038/s41746-021-00553-x

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