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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...
Formato: | Online Artículo Texto |
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Lenguaje: | English |
Publicado: |
IEEE
2020
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Materias: | |
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 |
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