Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validation

• Príomhchruthaitheoirí: Ting Dang (Údar), Jing Han (Údar), Tong Xia (Údar), Dimitris Spathis (Údar), Erika Bondareva (Údar), Chloë Siegele-Brown (Údar), Jagmohan Chauhan (Údar), Andreas Grammenos (Údar), Apinan Hasthanasombat (Údar), R Andres Floto (Údar), Pietro Cicuta (Údar), Cecilia Mascolo (Údar)
• Formáid: LEABHAR
• Foilsithe / Cruthaithe: JMIR Publications, 2022-06-01T00:00:00Z.
• Ábhair: article
• Rochtain ar líne: Connect to this object online.

BackgroundRecent 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 and detect the infection, given the current audio sample, but do not monitor disease progression in COVID-19. L...