Distinguish coronavirus disease from seasonal influenza using deep learning algorithm

Abstract

With the increasing number of cases of Corona virus, and with the availability of vaccines with virus Corona, the virus has not yet been controlled, and this may be due to certain reasons. The person who took the vaccine, if the vaccine was less immune may be a virus carrier, and this in turn may be the cause of the spread of the infection. The large artery of humans may not be committed to prevention if the vaccine is taken and this also leads to infection, especially we did not find from the global medical team of boots that whoever took the vaccine will never get infected again. Among the resources already in place, widely available and low-cost, the research proposes building an artificial intelligence system (supervised deep learning) to make a preliminary diagnosis of patients who are unaware of virus infection and to know the type of virus whether it is light, medium or dangerous and distinguish it from other diseases whose symptoms are similar to corona virus symptoms such as respiratory diseases, seasonal flu virus infections, kidney diseases, heart disease, nervous system diseases, diseases of the reproductive system. With the capacity of the research space and the parameters of the publication selectors, we will only take the regular seasonal flu as examples of research in the hope that we will complete other diseases and the extent to which they overlap with the Corona virus in the upcoming research hopefully. In this research, we will build an artificial intelligence system and simulate it through the application (supervised deep learning) to reach the accuracy of the diagnosis and safe isolation of people who do not know whether they are infected or not, and determine the type of infection virus, in turn reduces the spread of infection and also help the medical staff who suffered the scourges due to this virus after taking many lives.