Long short-term memory-based forecasting of influenza epidemics using surveillance and meteorological data in Tokyo, Japan

This study highlighted the efficacy of LSTM-based models for short-term influenza forecasting and reinforces the importance of integrating meteorological variables and national public holidays into predictive frameworks. Our optimal model provided more precise forecasts of influenza activity in Tokyo, Japan.