Predicting death and confirmed cases of coronavirus

At the end of 2019, a new virus called coronavirus has globally spread causing severe effections. In this paper, an artificial intelligence (AI) method is proposed to predict numbers death and confirmed cases. Efficient machine learning (ML) network named byesian regularization backpropagation (BRB) employed. It can estimates cases from applied population density date. So, BRB uses density, month day as inputs, predicts per million deaths outputs. The was trained assessed by using daily recorded dataset known our world in data (OWID). considered dates here are 31st December 2019 13th October 2020. Furthermore, information countries over all obtained results provided good promising performance with testing mean absolute error (MAE) equal 0.0218.