The world has witnessed the most devastating pandemic due to the rapid
spread of COVID-19, an infectious disease caused by severe acute respiratory
syndrome coronavirus (SARS-CoV2 virus). The public health emergency of
international concern arose due to the sudden outbreak of COVID-19 where both
medical and socio-economic structures remain entirely altered not only in developed
countries but also in developing countries. In this crucial scenario, advanced
technologies like machine learning (ML) and deep learning (DL) assisted the
researchers and helped governments and other health officials (including frontline
workers) to manage the outbreak. ML is a sub-branch of computer science, where,
machines can analyze large datasets and derive inference from that variable data
structures. With the help of suitable algorithms, computers can imitate human behavior
by analyzing results and the machines can perform in less time with great accuracy.
During the pandemic, due to the scarcity of human resources, ML aided in the
diagnosis of patients, forecasted communal transmission, and also helped in the
development of effective antivirals and vaccines. In this chapter, we have highlighted
the importance of various state-of-the-art ML tools, algorithms and computational
models useful in the diagnosis and management of COVID-19. The circumstantial
applications of ML are also discussed with real-time case studies. Lastly, the
challenges faced by ML in COVID-19 supervision and future directions are also
discussed. This chapter will help the researchers and students to understand how this
powerful tool is employed to fight COVID-19 and can assist in future health
emergencies due to emerging pathogens.
Keywords: Computers, Computational models, COVID-19, Deep learning, ML, Socio-economic, SARS-CoV-2, Vaccine development.
