A Novel Data-Driven Model for Real-Time Influenza Forecasting

A Novel Data-Driven Model for Real-Time Influenza Forecasting

We propose a novel data-driven machine learning method using long short-term memory (LSTM)-based multi-stage forecasting for influenza forecasting. The novel aspects of the method include the following: 1) the introduction of LSTM method to capture the temporal dynamics of seasonal flu and 2) a tech...

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Bibliographic Details
Main Authors: Siva R. Venna, Amirhossein Tavanaei, Raju N. Gottumukkala, Vijay V. Raghavan, Anthony S. Maida, Stephen Nichols
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Influenza forecasting
LSTM
recurrent neural networks
spatio-temporal data
time series forecasting
Online Access:https://ieeexplore.ieee.org/document/8581423/

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