COVID-19 Death Risk Assessment in Iran using Artificial Neural Network

Abstract Since the pandemic spread of COVID-19, it has posed a unique public health concern worldwide due to its increased death rate all around world. The disease is caused by SARS-CoV-2, which main cause Middle East Respiratory Syndrome (MERS) and severe acute respiratory syndrome (SARS). Risk assessment vital action toward risk reduction as increases understanding factors associated with allows existing data decide on adequate preventive mitigation measures. Machine learning techniques have gained strength since 2000, crucial role in analysis really helpful develop standard mortality models. This study aims find best model for using Artificial Neural Network (ANN) other factors, contribute high morbidity COVID-19 Iran, predict people different situation. A systematic review meta-analysis were examined patient factor from studies done researchers estimate risk. extracted an study. Using ANN, prediction calculated. Assessment number hidden neurons training function Bayesian Regularization algorithm, ANN 5 found most satisfying results. coefficient determination (R) Root Mean Square Error (RMSE) was 9.99999e-1 4.54201e-19 respectively.