This paper is in the following e-collection/theme issue:

Short Paper (23) Data Science (270) JMIR Theme Issue: COVID-19 Special Issue (2452) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) New Methods (944) Artificial Intelligence (1371) Development of Novel Medical Devices and Innovations for Existing Devices (80) Artificial Intelligence (86)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51640, first published .
Limitations of the Cough Sound-Based COVID-19 Diagnosis Artificial Intelligence Model and its Future Direction: Longitudinal Observation Study

Limitations of the Cough Sound-Based COVID-19 Diagnosis Artificial Intelligence Model and its Future Direction: Longitudinal Observation Study

Limitations of the Cough Sound-Based COVID-19 Diagnosis Artificial Intelligence Model and its Future Direction: Longitudinal Observation Study

Authors of this article:

Jina Kim1 Author Orcid Image ;   Yong Sung Choi1 Author Orcid Image ;   Young Joo Lee1 Author Orcid Image ;   Seung Geun Yeo1 Author Orcid Image ;   Kyung Won Kim2 Author Orcid Image ;   Min Seo Kim3 Author Orcid Image ;   Masoud Rahmati4, 5 Author Orcid Image ;   Dong Keon Yon6, 7 Author Orcid Image ;   Jinseok Lee1, 8 Author Orcid Image
Article Authors Cited by (1) Tweetations (4) Metrics

Journals

  1. Kim Y, Kim S, Lee S, Park J, Koyanagi A, Smith L, Kim M, Fond G, Boyer L, López Sánchez G, Dragioti E, Kim H, Lee H, Son Y, Kim M, Kim S, Yon D. National Trends in the Prevalence of Unmet Health Care and Dental Care Needs During the COVID-19 Pandemic: Longitudinal Study in South Korea, 2009-2022. JMIR Public Health and Surveillance 2024;10:e51481 View