Rapid
changes
in
medical
education
are
being
fueled
by
advancements
science,
technology,
and
societal
structures.
However,
the
traditional
curriculum
often
struggles
to
keep
pace
with
evolving
demands
of
practice
light
these
advancements.
Neurology
presents
distinctive
challenges
modern
medicine,
requiring
innovative
solutions
improve
patient
care
support
well-being
healthcare
providers.
This
essay
delves
into
intricate
issues
encountered
neurologists,
such
as
diminishing
interpersonal
connections
field
prevalent
issue
burnout
among
professionals,
exacerbated
outdated
educational
programs.
research
advocates
for
a
comprehensive
approach
enhancing
neurology
through
perspectives
Medical
Humanities
(MH)
neurobiology,
within
realm
Neurohumanities.
By
integrating
state-of-the-art
neurobiological
findings,
MH/Neurohumanities,
focus
on
empathy,
article
proposes
practical
strategies
rejuvenate
clinical
bolster
resilience
practitioners.
Furthermore,
it
underscores
untapped
potential
artificial
intelligence
machine
learning
while
examining
how
digital
ecosystem
could
revolutionize
education.
Grounded
evidence-based
insights,
this
offers
valuable
guidance
navigating
complexities
contemporary
cultivating
workforce
professionals
who
possess
both
technological
acumen
compassion.
Cerebrovascular
accidents
(CVAs)
often
occur
suddenly
and
abruptly,
leaving
patients
with
long-lasting
disabilities
that
place
a
huge
emotional
economic
burden
on
everyone
involved.
CVAs
result
when
emboli
or
thrombi
travel
to
the
brain
impede
blood
flow;
subsequent
lack
of
oxygen
supply
leads
ischemia
eventually
tissue
infarction.
The
most
important
factor
determining
prognosis
CVA
is
time,
specifically
time
from
onset
disease
treatment.
Artificial
intelligence
(AI)-assisted
neuroimaging
alleviates
constraints
analysis
faced
using
traditional
diagnostic
imaging
modalities,
thus
shortening
diagnosis
Numerous
recent
studies
support
increased
accuracy
processing
capabilities
AI-assisted
modalities.
However,
learning
curve
steep,
barriers
still
exist
preventing
full-scale
implementation
this
technology.
Thus,
potential
for
AI
revolutionize
medicine
healthcare
delivery
demands
attention.
This
paper
aims
elucidate
progress
AI-powered
in
while
considering
techniques
suggesting
methods
overcome
adoption
hope
will
be
considered
normal
practice
near
future.
There
are
multiple
modalities
neuroimaging,
all
which
require
collecting
sufficient
data
establish
inclusive,
accurate,
uniform
detection
platforms.
Future
efforts
must
focus
developing
harmonization
standardization.
Furthermore,
transparency
explainability
these
technologies
needs
established
facilitate
trust
between
physicians
necessitates
considerable
resources,
both
financial
expertise
wise
not
available
everywhere.
PLoS ONE,
Год журнала:
2024,
Номер
19(10), С. e0310028 - e0310028
Опубликована: Окт. 9, 2024
ChatGPT,
a
general
artificial
intelligence,
has
been
recognized
as
powerful
tool
in
scientific
writing
and
programming
but
its
use
medical
is
largely
overlooked.
The
accessibility,
rapid
response
time
comprehensive
training
database
might
enable
ChatGPT
to
serve
diagnostic
augmentation
certain
clinical
settings.
process
neurology
often
challenging
complex.
In
time-sensitive
scenarios,
evaluation
decisions
are
needed,
while
other
cases
clinicians
faced
with
rare
disorders
atypical
disease
manifestations.
Due
these
factors,
the
accuracy
suboptimal.
Here
we
evaluated
whether
can
be
utilized
valuable
innovative
various
neurological
We
used
synthetic
data
generated
by
experts
represent
descriptive
anamneses
of
patients
known
neurology-related
diseases,
then
probability
for
an
appropriate
diagnosis
made
was
measured.
To
give
clarity
AI-determined
diagnosis,
all
have
cross-validated
doctors
well.
found
that
ChatGPT-determined
(ranging
from
68.5%
±
3.28%
83.83%
2.73%)
reach
(81.66%
2.02%),
furthermore,
it
surpasses
if
examiner
doctor
(57.15%
2.64%).
Our
results
showcase
efficacy
intelligence
like
medicine.
future,
AI-based
supporting
tools
useful
amendments
practice
help
improve
neurology.
The
paper
presents
the
mathematical
modeling
and
analysis
of
LegUp,
a
novel
parallel
robotic
system
for
lower
limb
rehabilitation
bedridden
patients.
operational
workspace
is
defined
based
on
set
parameters
that
describe
motion
anatomic
joints,
which
natural
in
task.
To
comply
with
this
representation
workspace,
robot
kinematic
models
dependency
between
actuators
joints
limb.
Furthermore,
singularity
achieved
joint
space,
shows
whether
singularity-free.
achieve
feasible
mechanical
design
prescribed
to
ensure
safe
operation,
are
determined
multi-objective
optimization
problem.
Numerical
simulations
show
singularity-free
selected
parameters,
then
used
construct
experimental
model
LegUp.
Rapid
changes
in
medical
education
are
being
fueled
by
advancements
science,
technology,
and
societal
structures.
However,
the
traditional
curriculum
often
struggles
to
keep
pace
with
evolving
demands
of
practice
light
these
advancements.
Neurology
presents
distinctive
challenges
modern
medicine,
requiring
innovative
solutions
improve
patient
care
support
well-being
healthcare
providers.
This
essay
delves
into
intricate
issues
encountered
neurologists,
such
as
diminishing
interpersonal
connections
field
prevalent
issue
burnout
among
professionals,
exacerbated
outdated
educational
programs.
research
advocates
for
a
comprehensive
approach
enhancing
neurology
through
perspectives
Medical
Humanities
(MH)
neurobiology,
within
realm
Neurohumanities.
By
integrating
state-of-the-art
neurobiological
findings,
MH/Neurohumanities,
focus
on
empathy,
article
proposes
practical
strategies
rejuvenate
clinical
bolster
resilience
practitioners.
Furthermore,
it
underscores
untapped
potential
artificial
intelligence
machine
learning
while
examining
how
digital
ecosystem
could
revolutionize
education.
Grounded
evidence-based
insights,
this
offers
valuable
guidance
navigating
complexities
contemporary
cultivating
workforce
professionals
who
possess
both
technological
acumen
compassion.
