Application of deep learning approach for COVID-19 cases forecasting

Abstract

Abstract COVID - 19 , also Brown as the coronavirus , has paralyzed the whole world , infected more than 520 million people worldwide , and caused the death of more than 6 million people . Over the past few decades , the field of artificial intelligence and deep learning has shown tremendous development and multiple uses in many fields such as security , self - driving cars , robotics , and especially healthcare ... The enormous impact of this pandemic has prompted us to try to find and explore ways to use this technology to help limit its spread We proposed a method using long - short term memory ( LSTM ) a type of recurrent neural network ( RNN ) to predict the number of cases in the near future by using the information we have from previous cases since the beginning of the epidemic .