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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Veröffentlicht in:ArXiv
Hauptverfasser: Liu, Dianbo, Clemente, Leonardo, Poirier, Canelle, Ding, Xiyu, Chinazzi, Matteo, Davis, Jessica T, Vespignani, Alessandro, Santillana, Mauricio
Format: Artigo
Sprache:Inglês
Veröffentlicht: Cornell University 2020
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Article
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7280902/
https://ncbi.nlm.nih.gov/pubmed/32550248
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