For the third time in the last few decades, novel coronavirus-19 (2019-nCoV
or COVID-19) has been described as the most fatal coronavirus ever, capable of
infecting not just animals but even humans all over the world. Healthcare policy makes
use of advanced technologies such as artificial intelligence (AI), big data, the internet
of things (IoT), and deep machine learning to tackle and forecast emerging diseases. AI
is increasingly being used to help in disease identification, prevention, reaction,
rehabilitation, and clinical analysis. Since these developments are currently in their
initial phases of development, slow improvement in their application for significant
deliberation at local and foreign strategy levels is being made. Nevertheless, a current
case shows that AI-driven technologies are improving in reliability. Companies like
BlueDot and Metabiota used AI technology to predict the coronavirus disease-19
(COVID-19) in China before it surprised the world in late 2019 by spying on its effects
and propagation. One approach is to use computational techniques to discover new
target drugs and vaccines in silico. Machine learning-based algorithms trained on
particular biomolecules have provided affordable and quick-to-implement tools for the
development of successful viral treatments during the last decade. Drug repurposing is
a technique for finding new uses for accepted or experimental drugs. For novel diseases
like COVID-19, a drug repurposing approach is a viable approach. Future directions of
AI are drug discovery and vaccination, biological research, remote video diagnosis,
tracking patient contacts, COVID-19 recognition and therapy via smart robots, and
identification of non-contact infection. This chapter aims to explore AI-based technology for diagnosis, management, drug repurposing medications, novel drug discovery,
and vaccines for coronaviruses (SARS-CoV and MERS), including during the COVID19 pandemic.
Keywords: Artificial intelligence, Drug, MERS, SARS-CoV, SARS-CoV-2.
