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

Infodemiology and Infoveillance (1369) Outbreak and Pandemic Preparedness and Management (1742) mHealth for Data Collection and Research (979) Machine Learning (1493) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (39) Information Retrieval (296) Theoretical Frameworks and Concepts (261)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63476, first published .
Discovering Time-Varying Public Interest for COVID-19 Case Prediction in South Korea Using Search Engine Queries: Infodemiology Study

Discovering Time-Varying Public Interest for COVID-19 Case Prediction in South Korea Using Search Engine Queries: Infodemiology Study

Discovering Time-Varying Public Interest for COVID-19 Case Prediction in South Korea Using Search Engine Queries: Infodemiology Study

Authors of this article:

Seong-Ho Ahn1 Author Orcid Image ;   Kwangil Yim2 Author Orcid Image ;   Hyun-Sik Won1 Author Orcid Image ;   Kang-Min Kim1, 3 Author Orcid Image ;   Dong-Hwa Jeong1, 4 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Seong-Ho Ahn   1 * ;   Kwangil Yim   2 * , MD, PhD ;   Hyun-Sik Won   1 , MS ;   Kang-Min Kim   1, 3 * , PhD ;   Dong-Hwa Jeong   1, 4 * , PhD

1 Department of Artificial Intelligence, The Catholic University of Korea, Bucheon-Si, Republic of Korea

2 Department of Hospital Pathology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea

3 Department of Data Science, The Catholic University of Korea, Bucheon-Si, Republic of Korea

4 Department of Healthcare and Aritifical Intelligence, The Catholic University of Korea, Bucheon-Si, Republic of Korea

*these authors contributed equally

Corresponding Author: