Effective
public
health
surveillance
is
basic
to
rapidly
distinguish
and
react
developing
well-being
issues.
This
article
analyzes
the
benefits
suggestions
of
collaboration
between
epidemiologists
available
specialists
move
forward
with
administrations.
Through
a
subjective
writing
survey
investigation
strategies,
comes
about,
discoveries,
this
investigates
each
discipline's
commitment
moving
assessment.
Key
discoveries
are
examined,
counting
challenges
openings
recognized
in
past
thinks
about
assessments.
Furthermore,
proposals
were
made
progress
professionals
outcomes.
Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(22), P. 10144 - 10144
Published: Nov. 6, 2024
The
integration
of
artificial
intelligence
(AI)
in
healthcare
management
marks
a
significant
advance
technological
innovation,
promising
transformative
effects
on
processes,
patient
care,
and
the
efficacy
emergency
responses.
scientific
novelty
study
lies
its
integrated
approach,
combining
systematic
review
predictive
algorithms
to
provide
comprehensive
understanding
AI’s
role
improving
across
different
contexts.
Covering
period
between
2019
2023,
which
includes
global
challenges
posed
by
COVID-19
pandemic,
this
research
investigates
operational,
strategic,
response
implications
AI
adoption
sector.
It
further
examines
how
impact
varies
temporal
geographical
addresses
two
main
objectives:
explore
influences
domains,
identify
variations
based
Utilizing
an
we
compared
various
prediction
algorithms,
including
logistic
regression,
interpreted
results
through
SHAP
(SHapley
Additive
exPlanations)
analysis.
findings
reveal
five
key
thematic
areas:
enhancing
quality
assurance,
resource
management,
security,
pandemic.
highlights
positive
influence
operational
efficiency
strategic
decision
making,
while
also
identifying
related
data
privacy,
ethical
considerations,
need
for
ongoing
integration.
These
insights
opportunities
targeted
interventions
optimize
current
future
landscapes.
In
conclusion,
work
contributes
deeper
provides
policymakers,
professionals,
researchers,
offering
roadmap
addressing
both
IEEE Transactions on Engineering Management,
Journal Year:
2024,
Volume and Issue:
71, P. 5600 - 5615
Published: Jan. 1, 2024
Apparel
industry
is
grappling
with
sustainability
challenges.
Research
in
this
domain
has
seen
significant
growth
over
the
past
five
years.
However,
a
clear
division
of
topics
within
field
found
lacking.
This
study
addresses
gap
by
examining
intersection
fashion
and
sustainability,
assessing
its
evolution,
characteristics
potential
research
topics.
The
aims
to
assess
literature
on
fashion,
ascertain
trends
provide
future
directions
as
well
implications.
Exhaustive
search
was
conducted
using
comprehensive
database
Scopus
considering
studies
before
February
2023,
earliest
having
been
published
1963.
resulting
sample
658
articles
analysed
topic
modelling
method
text
mining
R
software
Latent
Dirichlet
Allocation
covering
various
sustainable
from
manufacturing
marketing.
Results
analysis
revealed
that
purchase
intention
behaviour
are
at
top
output.
We
present
strategies
challenges
for
implementing
circular
economy
sector.
study,
best
our
knowledge,
first
apply
approach
examination
literature.
It
offers
interdisciplinary
assessment
research.
Advances in healthcare information systems and administration book series,
Journal Year:
2025,
Volume and Issue:
unknown, P. 291 - 322
Published: Jan. 17, 2025
Diabetes
Mellitus
(DM)
is
a
metabolic
disorder
when
the
sugar
level
in
blood
elevated
consistently.
The
presence
of
one
global
health
challenges,
several
research
works
focusing
on
early
detection
and
management
innovative
machine
learning
technologies
were
developed
recent
years.
In
this
book
chapter,
we
introduce
novel
approach
to
classify
diabetes
mellitus
by
leveraging
Internet
Medical
Things
(IoMT)
generative
AI
models.
IoT
devices
continuously
monitor
critical
data
transmit
them
central
model
for
analysis
preprocessing
done.
preprocessed
act
as
input
models
predict
diabetes.
imbalanced
dataset
converted
into
balanced
using
two
called
VAE
GAN.
We
used
five
ML
classification
kNN,
SVM,
DT,
LR
RF
with
boosting.
Hard
voting
performed
determine
final
class.
Our
experiment
result
shows
that
proposed
ensemble
produces
an
accuracy
81%
which
outperformed
other
model's
Decision Analytics Journal,
Journal Year:
2023,
Volume and Issue:
10, P. 100392 - 100392
Published: Dec. 27, 2023
Appointment
scheduling
is
critical
to
increasing
resource
utilization
and
operational
performance
in
various
industry
domains,
especially
healthcare.
Costs
care
for
several
serious
diseases
are
projected
grow
due
the
aging
population
rising
drug
prices.
Thus,
there
an
urgent
need
efficient
planning
reduce
expenses.
This
research
explores
ways
effectively
schedule
outpatient
chemotherapy
visits
with
multiple
appointments
requiring
different
resources.
The
study
aims
assess
impact
of
patient
no-shows
individual
stochastic
appointment
durations
determine
if
overbooking
viable
mitigate
adverse
effects
no-shows.
first
applies
artificial
neural
networks
(ANN)
calculate
no-show
probabilities
individualized
durations.
Then,
it
builds
optimization
models
that
use
ANN
models'
outcomes
visits.
schedules
obtained
from
these
assessed
using
simulation
analysis
identify
effectiveness
combat
produce
better
key
indicators.
