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Found 5 papers, 1 papers with code
Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States
The ongoing COVID-19 pandemic continues to affect communities around the world.
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.
Towards the Use of Neural Networks for Influenza Prediction at Multiple Spatial Resolutions
We introduce the use of a Gated Recurrent Unit (GRU) for influenza prediction at the state- and city-level in the US, and experiment with the inclusion of real-time flu-related Internet search data.
Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance
Accurate real-time monitoring systems of influenza outbreaks help public health officials make informed decisions that may help save lives.
Accurate estimation of influenza epidemics using Google search data via ARGO
Accurate real-time tracking of influenza outbreaks helps public health officials make timely and meaningful decisions that could save lives.
