50 citations · 92 across the 13 of their papers we have counts for
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cs.SD2022★ 32 cited
Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validation
Ting Dang, Jing Han, Tong Xia +9
Recent work has shown the potential of using audio data (eg, cough, breathing, and voice) in the screening for COVID-19. However, these approaches only focus on one-off detection a…
cs.SD2021★ 5 cited
Sounds of COVID-19: exploring realistic performance of audio-based digital testing
Jing Han, Tong Xia, Dimitris Spathis +9
Researchers have been battling with the question of how we can identify Coronavirus disease (COVID-19) cases efficiently, affordably and at scale. Recent work has shown how audio b…
cs.SD2021★ 2 cited
Uncertainty-Aware COVID-19 Detection from Imbalanced Sound Data
Tong Xia, Jing Han, Lorena Qendro +2
Recently, sound-based COVID-19 detection studies have shown great promise to achieve scalable and prompt digital pre-screening. However, there are still two unsolved issues hinderi…