Predictive and interpretable machine learning for COVID-19 resurgences: the role of SARS-CoV-2 variants in the post-pandemic era
Abstract Background Traditional COVID-19 forecasting often misses the rapid dynamics of viral competition, limiting timely ublic health responses. This study demonstrates the value of incorporating SARS-CoV-2 variant data into recurrent neural networks, using an interpretable, data-driven approach t...
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| Hoofdauteurs: | , , |
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| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
BMC
2025-12-01
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| Reeks: | BMC Infectious Diseases |
| Onderwerpen: | |
| Online toegang: | https://doi.org/10.1186/s12879-025-12366-4 |
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