A systematic comparison of unimodal and bimodal machine learning forecasts of COVID-19 case surges finds strong country and modality dependence, with no universal benefit from adding more data types.
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Investigating the effectiveness of multimodal data in forecasting SARS-COV-2 case surges
A systematic comparison of unimodal and bimodal machine learning forecasts of COVID-19 case surges finds strong country and modality dependence, with no universal benefit from adding more data types.