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

JMIR Theme Issue: COVID-19 Special Issue (2453) Machine Learning (1471) Infectious Diseases (non-STD/STI) (1576) Outbreak and Pandemic Preparedness and Management (1728) Statistical Methods for Surveillance and Population Health (156) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1518)

Published on in Vol 22, No 9 (2020): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19907, first published .
Real-World Implications of a Rapidly Responsive COVID-19 Spread Model with Time-Dependent Parameters via Deep Learning: Model Development and Validation

Real-World Implications of a Rapidly Responsive COVID-19 Spread Model with Time-Dependent Parameters via Deep Learning: Model Development and Validation

Real-World Implications of a Rapidly Responsive COVID-19 Spread Model with Time-Dependent Parameters via Deep Learning: Model Development and Validation

Authors of this article:

Se Young Jung1, 2 Author Orcid Image ;   Hyeontae Jo3 Author Orcid Image ;   Hwijae Son4 Author Orcid Image ;   Hyung Ju Hwang4 Author Orcid Image
Article Authors Cited by (10) Tweetations (2) Metrics

Se Young Jung   1, 2 * , MD, MPH ;   Hyeontae Jo   3 * , PhD ;   Hwijae Son   4 , MSc ;   Hyung Ju Hwang   4 , PhD

1 Office of eHealth Research and Business, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea

2 Department of Family Medicine, Seoul National University Bundang Hospital, Seongnam-si, Republic of Korea

3 Basic Science Research Institute, Pohang University of Science and Technology, Pohang, Republic of Korea

4 Department of Mathematics, Pohang University of Science and Technology, Pohang, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Hyung Ju Hwang, PhD
  • Department of Mathematics, Pohang University of Science and Technology
  • 77, Cheongam-ro, Nam-gu, Pohang-si
  • Gyeongsangbuk-do
  • Pohang, 37673
  • Republic of Korea
  • Phone: 82 542792056
  • Fax: 82 542792799
  • Email: hjhwang@postech.ac.kr