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.
COVID,
Journal Year:
2023,
Volume and Issue:
3(1), P. 90 - 123
Published: Jan. 16, 2023
In
the
ongoing
COVID-19
pandemic,
digital
technologies
have
played
a
vital
role
to
minimize
spread
of
COVID-19,
and
control
its
pitfalls
for
general
public.
Without
such
technologies,
bringing
pandemic
under
would
been
tricky
slow.
Consequently,
exploration
status,
devising
appropriate
mitigation
strategies
also
be
difficult.
this
paper,
we
present
comprehensive
analysis
community-beneficial
that
were
employed
fight
pandemic.
Specifically,
demonstrate
practical
applications
ten
major
effectively
served
mankind
in
different
ways
during
crisis.
We
chosen
these
based
on
their
technical
significance
large-scale
adoption
arena.
The
selected
are
Internet
Things
(IoT),
artificial
intelligence(AI),
natural
language
processing(NLP),
computer
vision
(CV),
blockchain
(BC),
federated
learning
(FL),
robotics,
tiny
machine
(TinyML),
edge
computing
(EC),
synthetic
data
(SD).
For
each
technology,
working
mechanism,
context
challenges
from
perspective
COVID-19.
Our
can
pave
way
understanding
roles
COVID-19-fighting
used
future
infectious
diseases
prevent
global
crises.
Moreover,
discuss
heterogeneous
significantly
contributed
addressing
multiple
aspects
when
fed
aforementioned
technologies.
To
best
authors’
knowledge,
is
pioneering
work
transformative
with
broader
coverage
studies
applications.
Administrative Sciences,
Journal Year:
2024,
Volume and Issue:
14(12), P. 316 - 316
Published: Nov. 28, 2024
The
advent
of
Artificial
Intelligence
(AI)
is
profoundly
transforming
organizational
landscapes,
significantly
influencing
work
practices
and
triggering
cultural
shifts.
This
study
explores
the
role
AI
in
reshaping
examines
resulting
transformation.
Through
a
systematic
literature
review,
this
synthesizes
existing
research
to
provide
comprehensive
understanding
AI’s
impact
on
landscapes.
A
review
was
conducted,
analyzing
peer-reviewed
articles,
books,
conference
papers
identify
key
themes
related
AI-driven
changes
practices,
including
automation,
decision
making,
employee
roles.
It
also
how
these
influence
culture,
particularly
shifts
toward
innovation,
agility,
continuous
learning,
alongside
challenges
like
resistance
change
ethical
concerns.
While
adoption
promises
benefits
such
as
enhanced
efficiency,
productivity,
it
presents
significant
alignment,
resistance,
concerns,
leadership
communication.
Effective
leadership,
transparent
communication,
investments
skills
development
emerge
pivotal
strategies
for
overcoming
obstacles
ensuring
successful
implementation.
findings
offer
insights
into
complex
interplay
between
transformation,
highlighting
gaps
current
suggesting
directions
future
studies.
serves
valuable
resource
academics
practitioners
seeking
understand
broader
implications
structures
culture.
Advances in public policy and administration (APPA) book series,
Journal Year:
2025,
Volume and Issue:
unknown, P. 95 - 122
Published: Feb. 14, 2025
This
chapter
examines
how
AI
might
alter
public
administration
by
improving
efficiency,
accessibility,
and
decision-making.
automates
ordinary
jobs,
freeing
up
servants
for
high-impact
work.
Predictive
analytics
improve
government
operations
offering
data-driven
insights
resource
allocation
preemptive
actions
in
healthcare,
urban
planning,
safety.
Chatbots
virtual
assistants
make
services
more
accessible
to
different
populations,
especially
those
with
linguistic
or
physical
obstacles.
The
also
highlights
the
ethical
operational
issues
of
administration.
Due
data
privacy,
security,
algorithmic
bias,
deployment
must
be
transparent,
accountable,
fair.
Public
entities
can
ethically
use
following
governance
guidelines
gaining
trust.
emphasizes
balanced
establish
an
inclusive,
efficient,
citizen-centered,
adaptable
sector.
Annals of Operations Research,
Journal Year:
2024,
Volume and Issue:
333(2-3), P. 517 - 532
Published: Feb. 1, 2024
The
data
revolution
transforms
operations,
innovation,
and
society
through
artificial
intelligence
advanced
analytics.
Data-driven
innovations
(DDI)
have
the
most
potential
to
tackle
global
challenges,
including
poverty,
healthcare,
climate
actions,
disaster
management,
gender
inequality,
peace
justice
others.
This
paper
identifies
sources
of
DDI
capabilities
address
various
challenges.
findings
show
three
major
foundations
capabilities:
market
orientation,
infrastructure
talent
orientation.
Theoretically,
these
highlight
role
dynamic
sense,
seize
transform
Practically,
we
present
guidelines
for
developing
in
an
agile
efficient
manner
that
is
fair
inclusive.
IGI Global eBooks,
Journal Year:
2025,
Volume and Issue:
unknown, P. 341 - 362
Published: Feb. 21, 2025
Success
is
often
viewed
as
a
distant,
elusive
goal,
reserved
for
select
few
who
possess
extraordinary
talent
or
luck.
However,
the
reality
that
success
built
upon
foundational
principles,
and
investing
time
understanding,
applying
these
principles
can
transform
aspirations
into
tangible
achievements
create
solid
groundwork
personal
professional
growth.
At
heart
of
any
successful
endeavor
lies
principle
self-awareness.
This
because
informs
decision-making
helps
in
setting
realistic
meaningful
goals.
By
acknowledging
one's
capabilities
limitations,
individuals
make
more
informed
choices,
focus
on
areas
where
they
excel,
address
needing
improvement.
introspective
process
also
aligning
goals
with
values,
ensuring
efforts
are
not
only
effective
but
fulfilling.
Complementing
self-awareness
continuous
learning.
In
an
adapt
grow
indispensable.
involves
active
skills,
experiences,
development,
interests.
IGI Global eBooks,
Journal Year:
2025,
Volume and Issue:
unknown, P. 377 - 408
Published: May 2, 2025
Background
information:
Real-time
AI
and
Digital
Twins
are
revolutionizing
mental
health
with
real-time
stress
detection.
With
improved
precision
in
physiological,
behavioral,
social
IoT
data,
scalable,
accurate,
privacy-preserving
systems
must
be
designed
for
diagnoses.
Objective:
Improvement
of
DTs
to
enhance
the
detection
accuracy,
data
enhancing
scalability,
privacy
diagnosis.
Methods:
adaptive
reinforcement
learning,
PCA,
gradient
boosting,
data.
During
cross-validation
accuracy
measures,
Bayesian
optimization
is
applied
hyperparameters
optimize
computational
efficiency.
Result:
The
framework
reduced
feature
redundancy
transmission
costs
by
35%
30%,
respectively,
obtained
a
correctness
99.5%
98%
F1-score.
Conclusion:
AI-driven
framework,
its
use
algorithms
evaluation
internationally.
Matrik Jurnal Manajemen Teknik Informatika dan Rekayasa Komputer,
Journal Year:
2024,
Volume and Issue:
23(3), P. 583 - 592
Published: June 18, 2024
Infectious
diseases
continue
to
pose
a
major
threat
global
public
health
and
require
early
detection
effective
response
strategies.
Despite
advances
in
information
technology
data
analysis,
the
full
potential
of
identifying
disease
patterns
trends
remains
underutilised.
This
study
aims
propose
comprehensive
new
mathematical
model
(new
method)
that
utilises
identify
infectious
by
exploring
data-driven
care
approaches
addressing
challenges
associated
with
diseases.
The
research
methods
used
are
exploratory
collection
analytical
development.
results
obtained
models
algorithms
consider
period,
time,
patterns,
dangerous
diseases,
statistical
recommendations.
Data
visualisation
in-depth
analysis
were
conducted
improve
ability
respond
threats
provide
better
decision-making
solutions
improving
outbreak
response,
as
well
preparedness
challenges.
contributes
practitioners
decision-makers.
Advances in medical diagnosis, treatment, and care (AMDTC) book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 41 - 56
Published: June 30, 2024
AI
is
rapidly
transforming
the
field
of
epidemiology.
This
chapter
explores
how
integrates
data
analysis,
predictive
modeling,
disease
surveillance,
and
diagnostic
tools
to
significantly
improve
public
health
outcomes.
AI-driven
methodologies
enhance
accuracy,
surveillance
efficiency,
aid
in
developing
better
models,
all
which
contribute
improved
strategies.
seamlessly
with
traditional
epidemiological
approaches,
paving
way
for
a
new
era
combating
infectious
diseases.
Advancements
hold
immense
promise
future
health,
possibilities
real-time
personalized
medicine,
more
accurate
modeling.
However,
broader
adoption
responsible
use
require
careful
consideration
ethical
issues,
privacy
concerns,
collaboration
among
stakeholders.
Ultimately,
leveraging
effectively
has
potential
outcomes,
ensure
equitable
access
healthcare,
global
preparedness
crises.
Revue d intelligence artificielle,
Journal Year:
2022,
Volume and Issue:
36(4), P. 519 - 528
Published: Aug. 31, 2022
Sentimental
Analysis
has
grown
as
a
significant
opinion
strategy
in
the
field
of
online
media
due
to
quick
information
development
and
internet
technologies.
This
research
will
play
an
important
role
for
recommendation
best
airline
Indian
passengers
prefer
appropriate
their
journey
also
useful
ministry
aviation.
In
this
study
we
have
gathered
different
tiny
texts
called
comments
from
social
traveling
websites
using
webharvy
data
fetcher
scraping
tool
related
six
top
rated
airlines.
The
main
problem
with
tweet
SA
(sentimental
analysis)
is
determining
sentiment
classifier
appropriately
classifying
tweets.
VADER
model
used
ratings
connect
lexical
characteristics
emotion
intensities.
research,
Hybrid
integrated
Adaboost
approach
(HMIAA)
proposed,
which
combines
basic
learning
SVM
forward-learning
ensemble
method
Gradient
Boosted
Tree
form
single
robust
or
model,
objective
improving
SCT
classification
technique)
efficiency
(performance)
accuracy.
findings
reveal
that
suggested
hybrid
integrating
technique
outperforms
other
classifiers.
After
completion
sentimental
analysis
all
datasets
can
recommend
airline.
