COVID-19, coronavirus, screening, cough sounds, pandemic
With the distinct possibility of COVID-19 persisting after vaccines get distributed, the need for robust, inexpensive, and accessible screening for potential COVID-19 infections becomes ever more critical. Although symptoms present differently in different socio-demographic groups [1,2], cough is still ubiquitously presented as one of the primary symptoms by severe and non-severe infections alike [3,4,5,7]. Using cough sounds, AI-guided tools are able to screen COVID-19 positive cases [6,8,9]. As a result, such tools help reduce health disparity, specifically in low-resource settings [10,11]. Our study explores a robust, inexpensive, and accessible model that screens for COVID-19 infections to help communities limit/reduce the virus's spread. Our preliminary results are encouraging.
Mamun, Muntasir and Rasmussen, Nicholas, "COVID-19 Screening using Cough Sounds" (2021). IdeaFest. 323.