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A spatiotemporal machine learning approach to forecasting COVID-19 incidence at the county level in the USA
With COVID-19 affecting every country globally and changing everyday life, the ability to forecast the spread of the disease is more important than any previous epidemic. The conventional methods of disease-spread modeling, compartmental models, are based on the assumption of spatiotemporal homogene...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760128/ https://www.ncbi.nlm.nih.gov/pubmed/35071733 http://dx.doi.org/10.1007/s41060-021-00295-9 |