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...

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Detalles Bibliográficos
Autores principales: Chew, Alvin Wei Ze, Wang, Ying, Zhang, Limao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Article
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

Internet

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

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