DeepCOVIDNet: An Interpretable Deep Learning Model for Predictive Surveillance of COVID-19 Using Heterogeneous Features and Their Interactions

In this paper, we propose a deep learning model to forecast the range of increase in COVID-19 infected cases in future days and we present a novel method to compute equidimensional representations of multivariate time series and multivariate spatial time series data. Using this novel method, the pro...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IEEE 2020
Materias:
Computers and Information Processing
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545302/
https://www.ncbi.nlm.nih.gov/pubmed/34786287
http://dx.doi.org/10.1109/ACCESS.2020.3019989

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545302/
https://www.ncbi.nlm.nih.gov/pubmed/34786287
http://dx.doi.org/10.1109/ACCESS.2020.3019989

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