ICST Transactions on Scalable Information Systems,
Journal Year:
2023,
Volume and Issue:
unknown
Published: Sept. 18, 2023
In
this
paper
we
investigated
about
the
potential
problems
occurring
worldwide,
regarding
social
networks
with
misleading
advertisements
where
some
authors
applied
artificial
intelligence
techniques
such
as:
Neural
as
mentioned
by
Guo,
Z.,
et.
al,
(2021),
sentiment
analysis,
Paschen
(2020),
Machine
learning,
Burkov
(2019)
cited
in
Kaufman
(2020)
and,
to
combat
fake
news
front
of
publications
study
were
able
identify
if
these
allow
solve
fear
that
people
feel
being
victims
or
videos
without
checking
concerning
covid-19.
conclusion,
it
was
possible
detail
used
did
not
manage
a
deep
way.
These
are
real-time
applications,
since
each
technique
is
separately,
extracting
data
from
information
networks,
generating
diagnoses
alerts.
Informatics in Medicine Unlocked,
Journal Year:
2023,
Volume and Issue:
38, P. 101199 - 101199
Published: Jan. 1, 2023
The
worldwide
spread
of
the
COVID-19
disease
has
had
a
catastrophic
effect
on
healthcare
supply
chains.
current
manuscript
systematically
analyzes
existing
studies
mitigating
strategies
for
disruption
management
in
chain
during
COVID-19.
Using
systematic
approach,
we
recognized
35
related
papers.
Artificial
intelligence
(AI),
block
chain,
big
data
analytics,
and
simulation
are
most
important
technologies
employed
healthcare.
findings
reveal
that
published
research
concentrated
mainly
generating
resilience
plans
impacts.
Furthermore,
vulnerability
chains
necessity
establishing
better
methods
emphasized
research.
However,
practical
application
these
emerging
tools
managing
disturbance
warranting
been
examined
only
rarely.
This
article
provides
directions
additional
research,
which
can
guide
researchers
to
develop
conduct
impressive
different
disasters.
Advances in medical technologies and clinical practice book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 250 - 264
Published: April 15, 2024
This
chapter
delves
into
the
transformative
effects
of
artificial
intelligence
(AI)
on
healthcare
diagnostics,
focusing
accuracy,
efficiency,
and
predictability.
The
thorough
analysis
is
organized
around
main
thematic
parts.
opens
with
an
informative
review
AI's
role
in
laying
groundwork
for
understanding
how
AI
technologies,
such
as
machine
learning
deep
learning,
transform
medical
diagnostic
processes.
history
procedures
explored,
emphasizing
transition
from
old
methods
to
current
era
AI-driven
approaches.
Finally,
this
presents
a
investigation
diagnostics
impact
healthcare's
future.
Covering
present
applications,
problems,
future
possibilities,
it
adds
greater
discussion
integration
healthcare.
It
emphasizes
importance
responsible
collaborative
growth
transformational
subject.
IGI Global eBooks,
Journal Year:
2025,
Volume and Issue:
unknown, P. 97 - 122
Published: Feb. 21, 2025
This
chapter
examines
how
artificial
intelligence
(AI)
is
changing
engineering
and
physical
science
researchers
do
their
work.
It
demonstrates
(AI)-driven
technologies—like
machine
learning
deep
predictive
analytics—are
transforming
conventional
approaches
by
making
it
possible
to
process
analyse
enormous
datasets
at
previously
unheard-of
speeds
precision.
In
fields
where
sophisticated
simulations
data
patterns
have
produced
ground-breaking
discoveries
such
as
materials
renewable
energy
aerospace
manufacturing
the
explores
integration
of
AI
in
these
fields.
also
discusses
can
stimulate
interdisciplinary
collaboration
increase
power
improve
research
efficiency.
The
covers
obstacles
requirement
for
transparent
algorithms
ethical
issues
biases.
usefulness
developments
demonstrated
through
case
studies
effective
applications
scientific
research.
Infectious Medicine,
Journal Year:
2024,
Volume and Issue:
3(1), P. 100095 - 100095
Published: Feb. 21, 2024
The
COVID-19
pandemic
has
created
unprecedented
challenges
worldwide.
Artificial
intelligence
(AI)
technologies
hold
tremendous
potential
for
tackling
key
aspects
of
management
and
response.
In
the
present
review,
we
discuss
possibilities
AI
technology
in
addressing
global
posed
by
pandemic.
First,
outline
multiple
impacts
current
on
public
health,
economy,
society.
Next,
focus
innovative
applications
advanced
areas
such
as
prediction,
detection,
control,
drug
discovery
treatment.
Specifically,
AI-based
predictive
analytics
models
can
use
clinical,
epidemiological,
omics
data
to
forecast
disease
spread
patient
outcomes.
Additionally,
deep
neural
networks
enable
rapid
diagnosis
through
medical
imaging.
Intelligent
systems
support
risk
assessment,
decision-making,
social
sensing,
thereby
improving
epidemic
control
health
policies.
Furthermore,
high-throughput
virtual
screening
enables
accelerate
identification
therapeutic
candidates
opportunities
repurposing.
Finally,
future
research
directions
combating
COVID-19,
emphasizing
importance
interdisciplinary
collaboration.
Though
promising,
barriers
related
model
generalization,
quality,
infrastructure
readiness,
ethical
risks
must
be
addressed
fully
translate
these
innovations
into
real-world
impacts.
Multidisciplinary
collaboration
engaging
diverse
expertise
stakeholders
is
imperative
developing
robust,
responsible,
human-centered
solutions
against
emergencies.
Advances in healthcare information systems and administration book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 77 - 94
Published: Nov. 22, 2024
This
chapter
investigates
the
groundbreaking
job
of
artificial
intelligence
driven
risk
forecast
models
in
improving
pandemic
readiness
and
worldwide
wellbeing
security.
AI
technologies
have
emerged
as
essential
tools
for
early
detection,
assessment,
management
infectious
disease
outbreaks
light
increasing
frequency
complexity
pandemics.
The
section
looks
at
how
computer-based
applications,
including
high-level
information
investigation,
empower
distinguishing
proof
possible
dangers,
prescient
displaying
infection
spread,
enhancement
general
reactions.
highlights
benefits
drawbacks
incorporating
into
preparedness
strategies
through
real-world
examples
case
studies.
Privacy
ethical
issues
are
also
discussed,
with
a
focus
on
necessity
using
responsibly
public
health.
Frontiers in Artificial Intelligence,
Journal Year:
2022,
Volume and Issue:
5
Published: May 27, 2022
Graphical-design-based
symptomatic
techniques
in
pandemics
perform
a
quintessential
purpose
screening
hit
causes
that
comparatively
render
better
outcomes
amongst
the
principal
radioscopy
mechanisms
recognizing
and
diagnosing
COVID-19
cases.
The
deep
learning
paradigm
has
been
applied
vastly
to
investigate
radiographic
images
such
as
Chest
X-Rays
(CXR)
CT
scan
images.
These
are
rich
information
patterns
clusters
like
structures,
which
evident
conformance
detection
of
pandemics.
This
paper
aims
comprehensively
study
analyze
methodology
based
on
Deep
for
diagnosis.
technology
is
good,
practical,
affordable
modality
can
be
deemed
reliable
technique
adequately
virus.
Furthermore,
research
determines
potential
enhance
image
character
through
artificial
intelligence
distinguishes
most
inexpensive
trustworthy
imaging
method
anticipate
dreadful
viruses.
further
discusses
cost-effectiveness
surveyed
methods
detecting
COVID-19,
contrast
with
other
methods.
Several
finance-related
aspects
effectiveness
different
used
have
discussed.
Overall,
this
presents
an
overview
using
their
financial
implications
from
perspective
insurance
claim
settlement.
International Journal of Management & Entrepreneurship Research,
Journal Year:
2023,
Volume and Issue:
4(12), P. 607 - 622
Published: Dec. 28, 2023
This
paper
review
ways
AI
and
analytics
are
transforming
HR
decision-making
in
American
organizations.
It
explores
the
adoption
of
these
technologies
U.S.,
their
impact
on
optimizing
talent
management,
broader
implications
for
organizational
growth
employee
well-being.
In
rapidly
evolving
landscape
Human
Resources
(HR),
integration
Artificial
Intelligence
(AI)-driven
has
emerged
as
a
transformative
force.
application
AI-driven
United
States,
specifically
focusing
its
role
strategic
decision-making.
The
analysis
delves
into
current
state
practices,
challenges
opportunities
it
presents,
performance.
Key
topics
covered
include
predictive
analytics,
acquisition,
workforce
planning,
engagement.
Through
comprehensive
examination
existing
literature
case
studies,
this
aims
to
provide
insights
shapes
decisions
contributes
success
U.S.
context.
findings
underscore
imperative
professionals
leaders
navigate
fostering
deeper
understanding
potential
benefits
informed
decision-making.
Keywords:
Intelligence;
Talent
Analytics;
Resources;
Decision-Making;
USA.
