World Journal of Clinical Cases,
Год журнала:
2024,
Номер
13(11)
Опубликована: Дек. 25, 2024
Patients
in
intensive
care
units
(ICUs)
require
rapid
critical
decision
making.
Modern
ICUs
are
data
rich,
where
information
streams
from
diverse
sources.
Machine
learning
(ML)
and
neural
networks
(NN)
can
leverage
the
rich
for
prognostication
clinical
care.
They
handle
complex
nonlinear
relationships
medical
have
advantages
over
traditional
predictive
methods.
A
number
of
models
used:
(1)
Feedforward
networks;
(2)
Recurrent
NN
convolutional
to
predict
key
outcomes
such
as
mortality,
length
stay
ICU
likelihood
complications.
Current
exist
silos;
their
integration
into
workflow
requires
greater
transparency
on
that
analyzed.
Most
accurate
enough
use
operate
'black-boxes'
which
logic
behind
making
is
opaque.
Advances
occurred
see
through
opacity
peer
processing
black-box.
In
near
future
ML
positioned
help
far
beyond
what
currently
possible.
Transparency
first
step
toward
validation
followed
by
trust
adoption.
summary,
NNs
transformative
ability
enhance
accuracy
improve
patient
management
ICUs.
The
concept
should
soon
be
turning
reality.
Small Structures,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 27, 2025
Conductive
hydrogels
provide
a
flexible
platform
technology
that
enables
the
development
of
personalized
materials
for
various
neuronal
diagnostic
and
therapeutic
applications,
combining
complementary
properties
conductive
hydrogels.
By
ensuring
conductivity
through
materials,
largely
compensate
rigidity
traditional
inorganic
making
them
suitable
substitute.
To
adapt
to
different
working
environments,
exhibit
excellent
properties,
such
as
mechanical
adhesion,
biocompatibility,
which
further
expand
their
applications.
This
review
summarizes
fabrication
methods,
applications
in
neural
interfaces.
Finally,
prevailing
challenges
outlines
future
directions
field
interfaces
are
provided,
emphasizing
need
interdisciplinary
research
address
issues
long‐term
stability
scalability
production.
Nano Trends,
Год журнала:
2024,
Номер
7, С. 100042 - 100042
Опубликована: Июнь 18, 2024
Piezoelectricity
has
emerged
as
a
pivotal
platform
technology
in
bioengineering
to
advance
cardiac
healthcare.
Unlike
common
pacemakers,
these
devices
capitalize
on
the
mechanical
energy
derived
from
movements
power
themselves,
presenting
sustainable
alternative
battery
constraints
faced
by
current
implantable
devices.
This
review
explores
advances
piezoelectric
nanogenerators
for
monitoring
and
therapy,
highlighting
their
capabilities
not
only
track
activity,
but
also
provide
therapeutic
interventions
reliable
pacemakers.
It
discusses
electric
stimulation
effects
biocompatible
integration
with
human
biology,
positioning
at
forefront
of
healthcare
solutions,
thereby
enhancing
effectiveness,
durability,
personalized
care.
Building
on
current
explorations
in
chronic
optical
neural
interfaces,
it
is
essential
to
address
the
risk
of
photothermal
damage
traditional
optogenetics.
By
focusing
calcium
fluorescence
for
imaging
rather
than
stimulation,
injectable
fluorescent
interfaces
significantly
minimize
and
improve
accuracy
neuronal
imaging.
Key
advancements
including
use
microelectronics
targeted
electrical
stimulation
their
integration
with
cell-specific
genetically
encoded
indicators
have
been
discussed.
These
electronics
that
allow
post-treatment
retrieval
offer
a
minimally
invasive
solution,
enhancing
both
usability
reliability.
Furthermore,
bioelectronics
enables
precise
recording
individual
neurons.
This
shift
not
only
minimizes
risks
such
as
conversion
but
also
boosts
safety,
specificity,
effectiveness
Embracing
these
represents
significant
leap
forward
biomedical
engineering
neuroscience,
paving
way
advanced
brain–machine
interfaces.
Biosensors,
Год журнала:
2024,
Номер
14(7), С. 330 - 330
Опубликована: Июль 4, 2024
The
continued
advancement
of
organic
electronic
technology
will
establish
electrochemical
transistors
as
pivotal
instruments
in
the
field
biological
detection.
Here,
we
present
a
comprehensive
review
state-of-the-art
and
advancements
use
biosensors.
This
provides
an
in-depth
analysis
diverse
modification
materials,
methods,
mechanisms
utilized
transistor-structured
biosensors
(OETBs)
for
selective
detection
wide
range
target
analyte
encompassing
electroactive
species,
electro-inactive
cancer
cells.
Recent
advances
OETBs
sensing
systems
wearable
implantable
applications
are
also
briefly
introduced.
Finally,
challenges
opportunities
discussed.
ACS Nano,
Год журнала:
2024,
Номер
18(37), С. 25465 - 25477
Опубликована: Сен. 3, 2024
Inflammatory
responses,
leading
to
fibrosis
and
potential
host
rejection,
significantly
hinder
the
long-term
success
widespread
adoption
of
biomedical
implants.
The
ability
control
investigated
macrophage
inflammatory
responses
at
implant-macrophage
interface
would
be
critical
for
reducing
chronic
inflammation
improving
tissue
integration.
Nonetheless,
systematic
investigation
how
surface
topography
affects
polarization
is
typically
complicated
by
restricted
complexity
accessible
nanostructures,
difficulties
in
achieving
exact
control,
biased
preselection
experimental
parameters.
In
response
these
problems,
we
developed
a
large-scale,
high-content
combinatorial
biophysical
cue
(CBC)
array
enabling
high-throughput
screening
(HTS)
effects
nanotopography
on
subsequent
processes.
Our
CBC
array,
created
utilizing
dynamic
laser
interference
lithography
(DLIL)
technology,
contains
over
1
million
nanotopographies,
ranging
from
nanolines
nanogrids
intricate
hierarchical
structures
with
dimensions
100
nm
several
microns.
Using
machine
learning
(ML)
based
Gaussian
process
regression
algorithm,
successfully
identified
certain
topographical
signals
that
either
repress
(pro-M2)
or
stimulate
(pro-M1)
polarization.
upscaling
nanotopographies
further
examination
has
shown
mechanisms
such
as
cytoskeletal
remodeling
ROCK-dependent
epigenetic
activation
mechanotransduction
pathways
regulating
fate.
Thus,
have
also
platform
combining
advanced
DLIL
nanofabrication
techniques,
HTS,
ML-driven
prediction
nanobio
interactions,
pathway
evaluation.
short,
our
technology
not
only
improves
investigate
understand
nanotopography-regulated
but
holds
great
guiding
design
nanostructured
coatings
therapeutic
biomaterials
Brain Sciences,
Год журнала:
2025,
Номер
15(1), С. 50 - 50
Опубликована: Янв. 7, 2025
Decoding
motor
intentions
from
electroencephalogram
(EEG)
signals
is
a
critical
component
of
imagery-based
brain-computer
interface
(MI-BCIs).
In
traditional
EEG
signal
classification,
effectively
utilizing
the
valuable
information
contained
within
crucial.
To
further
optimize
use
various
domains,
we
propose
novel
framework
based
on
multi-domain
feature
rotation
transformation
and
stacking
ensemble
for
classifying
MI
tasks.
Initially,
extract
features
Time
Domain,
Frequency
domain,
Time-Frequency
Spatial
Domain
signals,
perform
selection
each
domain
to
identify
significant
that
possess
strong
discriminative
capacity.
Subsequently,
local
transformations
are
applied
set
generate
rotated
set,
enhancing
representational
capacity
features.
Next,
were
fused
with
original
obtain
composite
domain.
Finally,
employ
approach,
where
prediction
results
base
classifiers
corresponding
different
undergo
linear
discriminant
analysis
dimensionality
reduction,
yielding
integration
as
input
meta-classifier
classification.
The
proposed
method
achieves
average
classification
accuracies
92.92%,
89.13%,
86.26%
BCI
Competition
III
Dataset
IVa,
IV
I,
2a,
respectively.
Experimental
show
in
this
paper
outperforms
several
existing
methods,
such
Common
Time-Frequency-Spatial
Patterns
Selective
Extract
Multi-View
Decomposed
Spatial,
terms
accuracy
robustness.
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 261 - 290
Опубликована: Фев. 5, 2025
The
purpose
of
this
book
chapter
is
to
investigate
how
a
(NSGA-II)
multi-objective
genetic
algorithm
might
be
utilized
optimize
the
execution
an
Internet
Things
(IoT)
temperature
monitoring
Box-Type
Solar
Cooker
(BTSC).
To
determine
best
set
output
parameters
for
IoT
box-type
solar
cooker,
are
used
perform
optimizations
Figureure
merits
(F2),
cooking
power,
cooker
efficiency,
and
final
water
temperature.
present
research
work
involved
development
Wi-Fi
module
system
integrated
with
smart
BTSC.
We
compare
values
response
variables
that
were
gathered
experimentally
predicted
by
NSGA-II.
found
quite
close
experimental
values.
This
indicates
optimization
method,
as
in
study,
has
very
good
prediction
performance.
According
findings
experiment,
at
which
pot
remained
stagnant
on
average
was
158°C.
It
determined
class
A
based
first
merit
(F1),
second
power
(P),
respectively
0.132,
0.359,
86.108
W.
Therefore,
thermal
efficiency
IoT-base
box
type
39.99%.
Optimize
performance
IoT-based
BTSC
providing
real-time
data
visualization,
ultimately
improving
their
reliability.
provides
educational
tool
promote
awareness
understanding
renewable
energy
sources
potential
benefits.
