Long short-term memory-based forecasting of influenza epidemics using surveillance and meteorological data in Tokyo, Japan
BackgroundInfluenza remains a significant public health challenge worldwide, necessitating robust forecasting models to facilitate timely interventions and resource allocation. The aim of this study was to develop a long short-term memory (LSTM)-based short-term forecasting model to accurately predi...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
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Frontiers Media S.A.
2025-08-01
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| Serie: | Frontiers in Public Health |
| Soggetti: | |
| Accesso online: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1618508/full |
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