Abstract
The effect of the COVID-19 pandemic has prompted a large number of
studies targeted at understanding, monitoring, and containing the disease. However, it
is still unclear whether the studies performed so far have filled existing knowledge
gaps. We used computational intelligence (CI)/Machine Learning (ML) technologies
and alliance areas to analyse this massive amount of information at scale. This chapter
assesses the scholarly progress and prominent research domains in the use of CI/ML
technologies in COVID-19 research, focusing on the specific literature on
computational intelligence and related fields that have been employed for “diagnosis
and treatment” of COVID-19 patients.The “Web of Science” database was used to
retrieve all existing and highly cited papers published up to November 2020. Based on
bibliometric indicators, a search query (“Computational Intelligence or Neural
Networks or Fuzzy Systems or Evolutionary Computation & Diagnosis or Treatment &
Coronavirus or Corona Virus or COVID-19”) was used to retrieve the data sets. The
growth of research publications, elements of research activities, publication patterns,
and research focus tendencies were computed using ‘Biblioshiny’ software and data
visualization software ‘VOS viewer.’ Further, bibliometric/scientometrics techniques
were incorporated to know the most productive countries, most preferred sources &
their impact, three-field plot, and the most cited papers. This analysis provides a
comprehensive overview of the “COVID-19” and CI-related research, helping
researchers, policymakers, and practitioners better understand COVID-19 related CI research and its possible practical impact. Future CI / ML Studies should be committed
to filling the gap between CI / ML research.
Keywords: Computational intelligence, Bibliometric study, China, Computational modelling, Corona virus, Coronavirus, COVID-19, Diagnosis, Diagnosis tools, Evolutionary computation, Fuzzy sets, Fuzzy systems, India, Machine learning, Neural networks, Pandemic, Scientometrics, Treatment, Visualization, Web of science.