A novel bidirectional LSTM deep learning approach for COVID-19 forecasting

COVID-19 has resulted in significant morbidity and mortality globally. We develop a model that uses data from thirty days before a fixed time point to forecast the daily number of new COVID-19 cases fourteen days later in the early stages of the pandemic. Various time-dependent factors including the...

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Detalles Bibliográficos
Autores principales: Aung, Nway Nway, Pang, Junxiong, Chua, Matthew Chin Heng, Tan, Hui Xing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589260/
https://www.ncbi.nlm.nih.gov/pubmed/37863921
http://dx.doi.org/10.1038/s41598-023-44924-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589260/
https://www.ncbi.nlm.nih.gov/pubmed/37863921
http://dx.doi.org/10.1038/s41598-023-44924-8

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