Predictions For COVID-19 With Deep Learning Models of Long Short-Term Memory (LSTM)

Abstract

COVID-19, one of the most contagious diseases and urgent threats in recent times, attracts attention across the globe to study the trend of infections and help predict when the pandemic will end. A reliable prediction will make states and citizens acknowledge possible consequences and benefits for the policymaker among the delicate balance of reopening and public safety. This chapter introduces a deep learning technique and long short-term memory (LSTM) to forecast the trend of COVID-19 in the United States. The dataset from the New York Times (NYT) of confirmed and deaths cases is utilized in the research. The results include discussion of the potential outcomes if extreme circumstances happen and the profound effect beyond the forecasting number.