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.
medRxiv, 2024–01
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
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.