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

• Главные авторы: Ting Dang (Автор), Jing Han (Автор), Tong Xia (Автор), Dimitris Spathis (Автор), Erika Bondareva (Автор), Chloë Siegele-Brown (Автор), Jagmohan Chauhan (Автор), Andreas Grammenos (Автор), Apinan Hasthanasombat (Автор), R Andres Floto (Автор), Pietro Cicuta (Автор), Cecilia Mascolo (Автор)
• Формат: ‌
• Опубликовано: JMIR Publications, 2022-06-01T00:00:00Z.
• Предметы: article
• Online-ссылка: 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...