Published on in Vol 10, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35622, first published .
Discovery and Analytical Validation of a Vocal Biomarker to Monitor Anosmia and Ageusia in Patients With COVID-19: Cross-sectional Study

Discovery and Analytical Validation of a Vocal Biomarker to Monitor Anosmia and Ageusia in Patients With COVID-19: Cross-sectional Study

Discovery and Analytical Validation of a Vocal Biomarker to Monitor Anosmia and Ageusia in Patients With COVID-19: Cross-sectional Study

Journals

  1. Fischer A, Aguayo G, Oustric P, Morin L, Larche J, Benoy C, Fagherazzi G. Co-Design of a Voice-Based Digital Health Solution to Monitor Persisting Symptoms Related to COVID-19 (UpcomingVoice Study): Protocol for a Mixed Methods Study. JMIR Research Protocols 2023;12:e46103 View
  2. Evangelista E, Kale R, McCutcheon D, Rameau A, Gelbard A, Powell M, Johns M, Law A, Song P, Naunheim M, Watts S, Bryson P, Crowson M, Pinto J, Bensoussan Y. Current Practices in Voice Data Collection and Limitations to Voice AI Research: A National Survey. The Laryngoscope 2024;134(3):1333 View
  3. Evangelista E, Bélisle‐Pipon J, Naunheim M, Powell M, Gallois H, Bensoussan Y. Voice as a Biomarker in Health‐Tech: Mapping the Evolving Landscape of Voice Biomarkers in the Start‐Up World. Otolaryngology–Head and Neck Surgery 2024;171(2):340 View
  4. Sjaelland N, Gramkow M, Hasselbalch S, Frederiksen K, Duraes J. Digital Biomarkers for the Assessment of Non-Cognitive Symptoms in Patients with Dementia with Lewy Bodies: A Systematic Review. Journal of Alzheimer's Disease 2024;100(2):431 View
  5. dos Santos M, Heckler W, Bavaresco R, Barbosa J. Machine learning applied to digital phenotyping: A systematic literature review and taxonomy. Computers in Human Behavior 2024;161:108422 View
  6. Fischer A, Aguayo G, Pinker I, Oustric P, Lachaise T, Wilmes P, Larché J, Benoy C, Fagherazzi G. Co-design of a voice-based app to monitor long COVID symptoms with its end-users: A mixed-method study. DIGITAL HEALTH 2024;10 View