A parallel-stream LSTM with a social-connectivity-based spatial feature (SPH) is claimed to beat CDC Forecast Hub ensembles for state-level COVID-19 hospitalization forecasts.
PLoS computational biology, 20 (5), e1011200
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Integrating Spatiotemporal Features in LSTM for Spatially Informed COVID-19 Hospitalization Forecasting
A parallel-stream LSTM with a social-connectivity-based spatial feature (SPH) is claimed to beat CDC Forecast Hub ensembles for state-level COVID-19 hospitalization forecasts.