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Correlating dynamic climate conditions and socioeconomic-governmental factors to spatiotemporal spread of COVID-19 via semantic segmentation deep learning analysis
In this study, we develop a deep learning model to forecast the transmission rate of COVID-19 globally, via a proposed G parameter, as a function of fused data features which encompass selected climate conditions, socioeconomic and restrictive governmental factors. A 2-step optimization process is a...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier Ltd.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8340571/ https://www.ncbi.nlm.nih.gov/pubmed/34377630 http://dx.doi.org/10.1016/j.scs.2021.103231 |