Prediction of COVID-19 cases by multifactor driven long short-term memory (LSTM) model

Abstract Since December 2019, cases of COVID-19 have spread globally, caused millions of deaths and huge economic losses. To investigate the impact of different factors and predict the future trend, this study collects relevant data for 15 countries, containing 44 features in about 900 days, which c...

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Hlavní autoři:	Yanwen Shao, Tsz Kin Wan, Kei Hang Katie Chan
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2025-02-01
Edice:	Scientific Reports
Témata:	COVID-19 Disease prediction Pandemic prevention policy LSTM Machine learning
On-line přístup:	https://doi.org/10.1038/s41598-025-86698-1
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