Coronavirus Pandemic: A Review of Different Machine Learning Approaches

ABSTRACT

Millions of individuals have been affected by coronavirus illness. The coronavirus epidemic offers a significant medical danger to the wider range of population. The COVID-19 disease outbreak and subsequent control strategies have created a global syndrome that has impacted all aspects of human life. The initial stage detection of COVID-19 has become a difficult task for all researchers and scientists. There exist various ML and Deep Learning techniques to detect COVID-19 disease. There are various stages of COVID-19, initially, it was spread by people who travelled from countries which were severely affected by Corona Virus. After some time, it entered the community transmission phase. The virus has different impact on different individuals and there is no known cure found for this disease. The virus shows immediate affect on certain individuals whereas on others it takes few days to weeks for the symptoms to show but on some people it does not show any symptoms. The most common symptoms are dry cough, fever, lung infection, etc. This paper provides information about the several tests available for the detection of COVID-19. This paper provides a detailed comparison among the deep learning (DL) and AI (artificial intelligence) based techniques which are used to detect COVID-19 diesease. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.