COVID-19 Infection Forecasting using LSTM-based Model

ABSTRACT

COVID-19 has now become one of the most severe and acute diseases worldwide. Novel Coronavirus transmission is characterized by its high speed and large social population base, making novel Coronavirus detection very difficult. Therefore, automatic detection systems should be implemented as an option for rapid diagnosis. Automated disease detection frameworks help physicians diagnose diseases with accurate, consistent, and rapid results, and reduce ethics. In this paper, we propose a deep learning method based on long-term Memory (LSTM) for automatic diagnosis of COVID-19 in combination with the existing prediction model SEIR. © 2022 SPIE.