IEEE Computational Intelligence Magazine - November 2020 - 8

Guest
Editorial

Vincent S. Tseng
National Chiao Tung University, TAIWAN
Stephen T.C. Wong
Houston Methodist Cancer Center, USA
Diane J. Cook
Washington State University, USA
Jiming Liu
Hong Kong Baptist University, CHINA

C

OVID-19 (COronaVIrus Disease
2019), announced by World
Health Organization (WHO) in
March 2020, has become a global pandemic in very short time and caused
infections on tens of millions of people
with hundreds of thousands of deaths,
which unfortunately are continuing to
rise. Not only are the healthcare systems worldwide under high threats,
but also the global economy were
damaged severely.
During the past few months, all
countries are pushing to develop novel
and effective solutions for coping with
this crisis by leveraging the resources
and efforts from the governments,
industry and academia.Various emerging
solutions and systems for combating
COVID-19 have been under development and deployment, ranging from fast
screening methods to accurate diagnosis
using different kinds of clinical data
(X-Ray, CT, vital signs, etc.), risk profiling, patient surveillance, propagation
modeling, dashboard visualization and
control, drug and vaccine design and
social analytics. Computational intelligence plays an important and crucial
role in building such kind of solutions
since it takes different kinds of computational intelligence technologies, like
Neural Networks, Fuzzy Systems and

Digital Object Identifier 10.1109/MCI.2020.3019872
Date of current version: 14 October 2020

8

This Fast-Track Special Issue is in line with the COVID-19
Initiative of IEEE CIS, aiming to present the latest
developments and insights in applying computational
intelligence approaches into practical applications for
combating COVID-19.
Evolutionary Computation, to deal with
the underlying challenges. Moreover,
integration of computational intelligence mechanisms with various types of
medical systems/devices is essential for
practical deployment in existing healthcare environments.
In light of the above observations, this
"Fast-Track Special Issue," which is in line
with the COVID-19 Initiative of IEEE
CIS, aims at soliciting high-quality articles
to share the latest developments and
insights in applying computational intelligence approaches into practical applications for combating COVID-19. The
overall goal of this special issue is to offer a
venue for researchers and practitioners
from academia and industry to present the
latest technologies and developments in
dealing with the challenges brought by
COVID-19, with the hope to enlighten
new and compelling solutions for combating COVID-19. We were successful in
attracting 32 submissions, which were
reviewed by at least three competent
independent referees and one editor. Following a rigorous peer review process,

IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE | NOVEMBER 2020

5 papers have been accepted for publication in this special issue.
The first paper, "Computational
Intelligence Techniques for Combating
COVID-19: A Survey" by V. Tseng et al.,
provides a comprehensive review and
categorization of the representative
research works on computational intelligence for fighting COVID-19. The collected literatures are categorized into
five principles of computational intelligence according to the methods used.
Meanwhile, a number of important
issues that potentially can be addressed
by computational intelligence techniques are listed and categorized. Based
on the properties and advantages of each
principle, the authors also point out
what kinds of issues could be but have
not yet been dealt with well. In particular, the authors provide insightful discussions for enlightening future research
directions such as hybrid models for
dealing with the problem of treatment
design. Furthermore, this article reports
several promising real-world software
tools that applied the computational
IEEE Computational Intelligence Magazine - November 2020

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