Automatic COVID-19 Diagnostic and Classification Intelligent System (ACDCIS)

Coronaviruses are a huge gathering of infections that can contaminate both creatures and people. An assortment of coronaviruses is known to cause respiratory infections in people, extending from the common cold to more extraordinary sicknesses such as the Center East Respiratory Disorder (MERS) and extraordinary intense respiratory disorder (SARS). COVID-19 is caused by a recently distinguished coronavirus. Recognizing and diagnosing these cases of respiratory infections and the COVID-19 infection has been troublesome for health associations. Therefore, in this research, we will develop an Automatic COVID-19 Diagnostic and Classification Intelligent System (ACDCIS) based on Machine Learning (ML). The proposed ACDCIS consists of two sub-systems the three-classifier system and two-classifier system. The two-classifier system is used to determine if the patient has a Covid-19 or not, while the three-classifier system is used to specify the type of infection COVID-19, bacterial infection, or virus pneumonia infection. The high accuracy of the proposed ACDCIS system will increase the speed of diagnosis.