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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BMJ Publishing Group
2022
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| Materias: | |
| 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 |