Malaria,
a
dangerous
disease
transmitted
through
mosquito
bites
and
caused
by
Plasmodium
parasites,
presents
substantial
threat
to
human
health.
The
primary
aim
is
streamline
the
process,
rendering
it
quicker,
more
straightforward,
highly
efficient.
foremost
objective
create
robust
computer
model
capable
of
swiftly
distinguishing
cells
in
thin
blood
samples
obtained
from
standard
microscope
slides.
These
will
be
categorized
as
either
infected
or
uninfected,
employing
advanced
image
processing
techniques
facilitate
prompt
effective
testing.
Additionally,
authors
intend
harness
capabilities
machine
learning
for
classifying
cell
images.
purpose
firmly
rooted
desire
enhance
accuracy
speed
malaria
diagnosis,
ultimately
contributing
early
identification
management
this
life-threatening
ailment.
SAGE Open,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Jan. 1, 2025
This
research
delves
into
the
factors
and
considerations
influencing
public’s
adoption
of
interactive
intelligent
health
promotion
equipment.
Utilizing
DEMATEL
method,
study
investigates
interrelations
significance
various
decision
criteria,
laying
groundwork
for
future
initiatives
promoting
such
The
objective
is
to
bolster
interest
in
recreational
sports,
enhance
physical
well-being,
alleviate
healthcare
burdens.
identifies
eight
primary
factors:
economic
traits,
personality
communication
behavior,
relative
advantage,
compatibility,
complexity,
observability,
social
support,
peer
relationships.
Through
comprehensive
analysis,
both
direct
indirect
impacts
these
are
examined,
along
with
computation
key
indicators.
Findings
suggest
that,
among
individuals
exercise
habits,
traits
perceived
benefits
product
pivotal
determining
their
Within
comfort
emerges
as
most
influential
criterion,
tending
influence
other
factors.
Similarly,
advantage
category,
personalization
stands
out
sub-criterion
a
ripple
effect
on
aspects.
Further
ANP
analysis
findings
highlights
characteristics
weighted
followed
by
traits.
Computational and Structural Biotechnology Journal,
Journal Year:
2025,
Volume and Issue:
27, P. 1578 - 1599
Published: Jan. 1, 2025
Recent
research
on
Polycystic
Ovary
Syndrome
(PCOS)
detection
increasingly
employs
intelligent
algorithms
to
assist
gynecologists
in
more
accurate
and
efficient
diagnoses.
However,
PCOS
faces
notable
challenges:
absence
of
standardized
feature
taxonomies,
limited
available
datasets,
insufficient
understanding
existing
tools'
capabilities.
This
paper
addresses
these
gaps
by
introducing
a
novel
analytical
framework
for
diagnostic
developing
comprehensive
taxonomy
comprising
108
features
across
8
categories.
Furthermore,
we
analyzed
datasets
assessed
current
tools.
Our
findings
reveal
that
12
publicly
accessible
cover
only
54%
the
identified
our
taxonomy.
These
frequently
lack
multimodal
integration,
regular
updates,
clear
license
information-constraints
potentially
limit
tool
development.
Additionally,
analysis
42
tools
identifies
several
limitations:
high
computational
resource
requirements,
inadequate
data
processing,
longitudinal
capabilities,
clinical
validation.
Based
observations,
highlight
critical
challenges
future
directions
advancing
Advances in medical technologies and clinical practice book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 192 - 216
Published: Feb. 23, 2024
The
application
of
AI
in
geriatric
healthcare
has
become
a
revolutionary
and
essential
solution
to
tackling
the
problems
faced
by
older
people.
An
important
step
toward
providing
patient-centered
cost-effective
treatment,
integration
will
ultimately
enhance
standard
life
for
This
chapter
is
systematic
review
rapidly
developing
field
applications
healthcare.
It
provides
thorough
analysis
impact
potential
technologies
addressing
needs
aging
population.
was
conducted
using
PRISMA
framework.
Thirty-three
articles
were
considered
final
from
which
five
themes
deduced.
study
facilitate
development
relevant
inclusive
solutions
individuals
hasten
possibility
greater
wellbeing
inclusion
adults
technological
innovativeness
facilities.
International Journal of ADVANCED AND APPLIED SCIENCES,
Journal Year:
2024,
Volume and Issue:
11(12), P. 225 - 231
Published: Dec. 1, 2024
Diabetes
mellitus,
a
global
health
concern,
includes
type
1
diabetes,
with
an
uncontrollable
risk,
and
2
where
risk
can
be
managed
through
lifestyle
modifications.
This
study
examines
the
impact
of
modifiable
factors—diet,
physical
activity,
body
mass
index
(BMI)—on
diabetes
development.
Using
fuzzy
logic,
binary
variables
from
healthcare
dataset
were
transformed
into
format,
generating
three
output
classes:
"no
risk,"
"possible
"diabetes
present."
The
intermediate
class,
serves
as
alert
for
adopting
healthier
lifestyles
to
mitigate
risk.
Machine
learning
was
applied
both
original
fuzzy-transformed
datasets.
While
provided
outputs
moderate
accuracy
higher
computation
times,
yielded
more
nuanced
predictions,
reduced
time,
improved
classifier
performance.
approach
enhances
assessment
supports
proactive
interventions.
