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Exploring feasibility of multivariate deep learning models in predicting COVID-19 epidemic
Title
Exploring feasibility of multivariate deep learning models in predicting COVID-19 epidemic
Author
Thill, Jean-Claude, Janies, Daniel, Chen, Shi, Paul, Rajib
Date Created
2021
Subjects--Topical
Deep learning (Machine learning), COVID-19 (Disease)
Description
Background: Mathematical models are powerful tools to study COVID-19. However, one fundamental challenge in current modeling approaches is the lack of accurate and comprehensive data. Complex epidemiological systems such as COVID-19 are especially...