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

JMIR Theme Issue: COVID-19 Special Issue (2452) Machine Learning (1465) Infectious Diseases (non-STD/STI) (1575) Outbreak and Pandemic Preparedness and Management (1728) Statistical Methods for Surveillance and Population Health (156) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517)

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

Altmetric

Altmetric discovers Social Media mentions. Click the ‘See more details’ link for a full report.

Dimensions

Dimensions discovers Citations. Click the ‘details’ link for a full report.

Metrics Since Publication

Download .csv
Daily | Monthly | Annually