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Application of a data-driven XGBoost model for the prediction of COVID-19 in the USA: a time-series study

OBJECTIVE: The COVID-19 outbreak was first reported in Wuhan, China, and has been acknowledged as a pandemic due to its rapid spread worldwide. Predicting the trend of COVID-19 is of great significance for its prevention. A comparison between the autoregressive integrated moving average (ARIMA) mode...

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Detalles Bibliográficos
Autores principales:	Fang, Zheng-gang, Yang, Shu-qin, Lv, Cai-xia, An, Shu-yi, Wu, Wei
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BMJ Publishing Group 2022
Materias:	Epidemiology
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9251895/ https://www.ncbi.nlm.nih.gov/pubmed/35777884 http://dx.doi.org/10.1136/bmjopen-2021-056685

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