Machine Learning Opportunities in Traumatic Brain Injury Patients
Indian Journal of Neurotrauma,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 10, 2025
Язык: Английский
Advances of Artificial Intelligence in Neuroimaging
Brain Sciences,
Год журнала:
2025,
Номер
15(4), С. 351 - 351
Опубликована: Март 28, 2025
Neuroimaging
[...]
Язык: Английский
Animal Models of Traumatic Brain Injury and Their Relevance in Clinical Settings
CNS Neuroscience & Therapeutics,
Год журнала:
2025,
Номер
31(4)
Опубликована: Апрель 1, 2025
ABSTRACT
Background
Traumatic
brain
injury
(TBI)
is
a
significant
concern
that
often
goes
overlooked,
resulting
from
various
factors
such
as
traffic
accidents,
violence,
military
services,
and
medical
conditions.
It
major
health
issue
affecting
people
of
all
age
groups
across
the
world,
causing
morbidity
mortality.
TBI
highly
intricate
disease
process
causes
both
structural
damage
functional
deficits.
These
effects
result
combination
primary
secondary
mechanisms.
responsible
for
range
negative
effects,
impairments
in
cognitive
function,
changes
social
behavioural
patterns,
difficulties
with
motor
skills,
feelings
anxiety,
symptoms
depression.
Methods
associated
animal
models
were
reviewed
databases
including
PubMed,
Web
Science,
Google
scholar
etc.
The
current
study
provides
comprehensive
overview
commonly
utilized
examines
their
potential
usefulness
clinical
context.
Results
Despite
notable
advancements
outcomes
over
past
two
decades,
there
remain
challenges
evaluating,
treating,
addressing
long‐term
prevention
this
condition.
Utilizing
experimental
crucial
gaining
insight
into
development
progression
TBI,
it
allows
us
to
examine
biochemical
impacts
on
Conclusion
This
exploration
can
assist
scientists
unraveling
mechanisms
involved
ultimately
contribute
advancement
successful
treatments
interventions
aimed
at
enhancing
patients.
Язык: Английский
Advanced neuromorphic engineering approaches for restoring neural activity after brain injury: innovations in regenerative medicine
Regenerative medicine reports .,
Год журнала:
2024,
Номер
1(2), С. 195 - 210
Опубликована: Дек. 1, 2024
Restoring
neural
function
after
brain
injury
is
a
critical
medical
challenge,
as
conventional
treatments
often
fail
to
achieve
full
recovery.
This
makes
the
development
of
innovative
regenerative
medicine
and
biomedical
engineering
strategies
particularly
necessary.
study
aims
fill
existing
gap
in
neuromorphic
by
mimicking
biological
neuron
dynamics
realizing
effective
clinical
applications
promote
functional
recovery
quality
life
enhancement
patients
with
injury.
The
novel
approaches
leverage
dynamic
behavior
neurons,
incorporating
electronic
circuits
that
emulate
neuronal
dynamics.
A
basic
configuration
involves
model
designed
mimic
living
neuron,
potential
replace
damaged
tissue
when
implanted,
thus
restoring
signal
propagation.
An
enhanced
integrates
closed-loop
system,
wherein
feedback
from
neurons
synchronizes
artificial
its
counterpart,
allowing
continuous
self-adjustment
system
parameters
promoting
neuro-autogenerative
regime.
Further
refinement
introduces
memristive
device
connects
simulate
synaptic
plasticity.
In
conjunction
control,
this
enables
self-tuning
for
improved
adaptability
natural
supporting
software
combines
nonlinear
deep
learning
techniques,
specifically
employing
reservoir
computing
performance.
These
were
successfully
validated
vitro
vivo
using
mice
models,
demonstrating
advanced
holds
significant
activity
offers
promising
strategy
improve
rehabilitation
outcomes
patients’
aiding
neurological
reconstruction.
Язык: Английский