Machine Learning-Driven Prediction of Vitamin D Deficiency Severity with Hybrid Optimization
Bioengineering,
Год журнала:
2025,
Номер
12(2), С. 200 - 200
Опубликована: Фев. 18, 2025
There
is
a
growing
need
to
predict
the
severity
of
vitamin
D
deficiency
(VDD)
through
non-invasive
methods
due
its
significant
global
health
concerns.
For
D-level
assessments,
25-hydroxy
(25-OH-D)
blood
test
standard,
but
it
often
not
practical
test.
This
study
focused
on
developing
machine
learning
(ML)
model
that
clinically
acceptable
for
accurately
detecting
status
and
eliminates
25-OH-D
determination
while
addressing
overfitting.
To
enhance
capacity
classification
system
multiple
classes,
preprocessing
procedures
such
as
data
reduction,
cleaning,
transformation
were
used
raw
dataset.
The
improved
whale
optimization
(IWOA)
algorithm
was
feature
selection,
which
optimized
weight
functions
improve
prediction
accuracy.
gauge
effectiveness
proposed
IWOA
algorithm,
evaluation
metrics
like
precision,
accuracy,
recall,
F1-score
used.
results
showed
99.4%
demonstrating
method
outperformed
others.
A
comparative
analysis
demonstrated
stacking
classifier
superior
choice
over
other
classifiers,
highlighting
robustness
in
deficiencies.
Incorporating
advanced
techniques,
method's
promise
generating
accurate
predictions
highlighted
study.
Язык: Английский
Mapping the landscape of vitamin D in cancer studies: a systematic global investigation
Journal of Diabetes & Metabolic Disorders,
Год журнала:
2025,
Номер
24(1)
Опубликована: Март 10, 2025
Язык: Английский
Cathelicidin: Insights into Its Impact on Metabolic Syndrome and Chronic Inflammation
Metabolites,
Год журнала:
2024,
Номер
14(12), С. 672 - 672
Опубликована: Дек. 2, 2024
Background/Objectives:
LL-37
is
associated
with
metabolic
syndrome
(MetS),
a
constellation
of
risk
factors
comprising
obesity,
insulin
resistance
(IR),
dyslipidemia,
and
hypertension,
which
elevates
the
cardiovascular
disease
type
2
diabetes.
Methods:
In
this
narrative
review,
we
analyzed
literature
focusing
on
recent
developments
in
relationship
between
cathelicidin
various
components
MetS
to
provide
comprehensive
overview.
Results:
Studies
have
shown
that
linked
inflammation
adipose
tissue
(AT)
development
IR
obesity.
Cathelicidin
can
enhance
by
activating
pro-inflammatory
genes,
as
well
modulate
inflammatory
response.
The
mechanisms
include
activation
complex
signaling
pathways
induce
reduce
adipocytes.
Toll-like
receptors
(TLRs)
stimulates
secretion
cytokines,
contributing
disruption
function
cells.
also
influences
lipid
metabolism,
research
showing
negative
levels
HDL
cholesterol.
Therefore,
involved
not
only
regulation
but
potentially
aggravating
complications
MetS.
Conclusions:
plays
crucial
role
regulating
balance
anti-inflammatory
responses
Understanding
impact
these
may
unveil
novel
approaches
for
addressing
its
complications.
Язык: Английский