BMC Medical Informatics and Decision Making,
Journal Year:
2024,
Volume and Issue:
24(1)
Published: Dec. 30, 2024
Major
underlying
health
issues
can
be
indicated
by
even
minor
nail
infections.
Subungual
Melanoma
is
one
of
the
most
severe
kinds
since
it
identified
at
a
much
later
stage
than
other
conditions.
The
purpose
this
research
to
offer
novel
deep-learning
algorithms
that
target
autonomous
categorization
six
forms
disorders
employing
images:
Blue
Finger,
Clubbing,
Pitting,
Onychogryphosis,
Acral
Lentiginous
Melanoma,
and
Normal
Nail
or
Healthy
Appearance.
Based
on
this,
we
build
an
initial
baseline
CNN
model,
which
then
further
advanced
introduction
Hybrid
Capsule
model
reduction
space
hierarchy
deficiencies
classic
model.
All
these
models
were
trained
tested
using
Disease
Detection
dataset
with
intensive
uses
techniques
data
augmentation.
thus,
provided
superior
classification
accuracy
compared
others;
training
was
99.40%,
while
validation
99.25%,
whereas
hybrid
outperformed
Base
astounding
precision,
recall
97.35%
96.79%.
additionally
leverages
capsule
network
dynamic
routing,
offering
improved
robustness
against
transformations
as
well
improving
spatial
properties.
current
study
consequently
provides
very
viable,
economical,
accessible
diagnostic
tool,
especially
for
places
paucity
medical
services.
proposed
methodology
tremendous
capacity
early
diagnosis
better
outcomes
patient
in
healthcare
scenario.
Clinical
trial
number
Not
applicable.
Luminescence,
Journal Year:
2025,
Volume and Issue:
40(2)
Published: Jan. 31, 2025
ABSTRACT
A
novel
fluorescence‐based
sensor
has
been
developed
for
the
sensitive
detection
of
malathion,
an
organophosphorus
pesticide,
using
sulfur‐doped
quantum
dots
(SQDs)
embedded
within
graphitic
carbon
nitride
(g‐C₃N₄)
nanosheets.
The
SQDs
were
synthesized
through
a
hydrothermal
method,
whereas
g‐C₃N₄
nanosheets
produced
via
exfoliation
process.
resulting
SQDs@g‐C₃N₄
nanocomposite
demonstrated
outstanding
performance
malathion
in
food
samples,
exhibiting
wide
linear
range
10–120
μM
and
exceptionally
low
limit
0.02
μM.
This
sensitivity
allows
accurate
rapid
pesticide
monitoring
at
trace
levels.
sensor's
was
optimized
by
varying
experimental
conditions,
ensuring
that
it
provided
high
sensitivity,
excellent
stability,
impressive
selectivity
toward
even
complex
matrices.
Symmetry,
Journal Year:
2025,
Volume and Issue:
17(1), P. 123 - 123
Published: Jan. 15, 2025
This
paper
introduces
a
kinetic
model
of
crowd
evacuation
from
bounded
domain,
integrating
social
behavior
and
contagion
dynamics.
The
describes
the
spatial
movement
individuals
in
crowd,
taking
into
account
interactions
with
other
people
geometry
environment.
Interactions
between
healthy
infectious
can
lead
to
disease
transmission
are
considered.
approach
is
grounded
theory
active
particles,
where
activity
variable
represents
both
status
(e.g.,
susceptible,
infected)
psychological
state
pedestrians,
including
awareness.
Varying
awareness
levels
influence
individual
behavior,
leading
more
cautious
patterns,
potentially
reducing
overall
infection
rate.
performance
evaluated
through
series
numerical
simulations.
Different
scenarios
examined
investigate
impact
on
pedestrian
spread,
times.
Additionally,
effects
population
immunization
assessed
determine
most
effective
strategy
for
infections.
results
provide
valuable
insights
targeted
strategies
mitigate
contagion.
Advanced Healthcare Materials,
Journal Year:
2024,
Volume and Issue:
13(29)
Published: June 25, 2024
Emerging
infectious
diseases
like
coronavirus
pneumonia
(COVID-19)
present
significant
challenges
to
global
health,
extensively
affecting
both
human
society
and
the
economy.
Extracellular
vesicles
(EVs)
have
demonstrated
remarkable
potential
as
crucial
biomedical
tools
for
COVID-19
diagnosis
treatment.
However,
due
limitations
in
performance
titer
of
natural
vesicles,
their
clinical
use
remains
limited.
Nonetheless,
EV-inspired
strategies
are
gaining
increasing
attention.
Notably,
biomimetic
inspired
by
EVs,
possess
specific
receptors
that
can
act
"Trojan
horses,"
preventing
virus
from
infecting
host
cells.
Genetic
engineering
enhance
these
enabling
them
carry
more
receptors,
significantly
specificity
absorbing
novel
coronavirus.
Additionally,
inherit
numerous
cytokine
parent
cells,
allowing
effectively
mitigate
"cytokine
storm"
adsorbing
pro-inflammatory
cytokines.
Overall,
this
strategy
offers
new
avenues
treatment
emerging
diseases.
Herein,
review
systematically
summarizes
current
applications
COVID-19.
The
status
associated
with
implementation
also
discussed.
goal
is
provide
insights
into
design
expand
application
combating
Polymers for Advanced Technologies,
Journal Year:
2024,
Volume and Issue:
35(12)
Published: Dec. 1, 2024
ABSTRACT
This
review
aims
to
provide
a
comprehensive
analysis
of
recent
advancements
in
smart
microneedles
(MNs)
within
the
biomedical
field,
focusing
on
integration
stimuli‐responsive
polymers
for
enhanced
therapeutic
and
diagnostic
applications.
Conventional
drug
delivery
methods
are
known
face
limitations
precision,
safety,
patient
compliance,
which
can
be
addressed
by
innovative
features
MNs.
Through
use
various
polymers,
these
MNs
have
been
designed
react
environmental
or
physiological
cues,
allowing
on‐demand
release,
biomarker
sensing,
localized
interventions.
Fundamental
materials
used
fabrication
MNs,
including
metals,
composite
hydrogels,
reviewed,
different
categories
stimuli‐responsiveness,
such
as
photo,
electro,
thermal,
mechanical,
biochemical,
explored.
Application‐specific
designs
areas
delivery,
cancer
therapy,
diabetes
management,
skin
disease
treatments
also
examined.
this
discussion,
it
is
highlighted
that
poised
play
significant
role
advancing
personalized
noninvasive
medical
treatments.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: Jan. 30, 2025
As
the
world
recovered
from
coronavirus,
emergence
of
monkeypox
virus
signaled
a
potential
new
pandemic,
highlighting
need
for
faster
and
more
efficient
diagnostic
methods.
This
study
introduces
hybrid
architecture
automatic
diagnosis
by
leveraging
modified
grey
wolf
optimization
model
effective
feature
selection
weighting.
Additionally,
system
uses
an
ensemble
classifiers,
incorporating
confusion
based
voting
scheme
to
combine
salient
data
features.
Evaluation
on
public
sets,
at
various
training
samples
percentages,
showed
that
proposed
strategy
achieves
promising
performance.
Namely,
yielded
overall
accuracy
98.91%
with
testing
run
time
5.5
seconds,
while
using
machine
classifiers
small
number
hyper-parameters.
Additional
experimental
comparison
reveals
superior
performance
over
literature
approaches
metrics.
Statistical
analysis
also
confirmed
AMDS
outperformed
other
models
after
running
50
times.
Finally,
generalizability
is
evaluated
its
external
sets
COVID-19.
Our
achieved
98.00%
99.00%
COVID
respectively.
