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A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models
We present a timely and novel methodology that combines disease estimates from mechanistic models with digital traces, via interpretable machine-learning methodologies, to reliably forecast COVID-19 activity in Chinese provinces in real-time. Specifically, our method is able to produce stable and ac...
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| Publicat a: | ArXiv |
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| Autors principals: | , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Cornell University
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7280902/ https://ncbi.nlm.nih.gov/pubmed/32550248 |
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