Administrative Sciences,
Год журнала:
2024,
Номер
14(9), С. 227 - 227
Опубликована: Сен. 17, 2024
Adopting
AI
(Artificial
Intelligence)
in
the
provision
of
psychiatric
services
has
been
groundbreaking
and
presented
other
means
handling
some
issues
related
to
traditional
methods.
This
paper
aims
at
analyzing
applicability
efficiency
mental
health
practices
based
on
business
administration
paradigms
with
a
focus
managing
policies.
engages
systematic
synoptic
process,
where
current
technologies
are
investigated
reference
literature
as
their
usefulness
delivering
moral
considerations
that
surround
application.
The
study
indicates
is
capable
improving
availability,
relevance,
effectiveness
services,
information
can
be
useful
for
policymakers
management
care.
Consequently,
specific
concerns
arise,
such
how
algorithm
imposes
its
own
bias,
question
data
privacy,
or
mechanism
could
reduce
human
factor
review
brought
light
an
area
understanding
AI-driven
interventions
not
explored:
effect
long
run.
field
suggests
further
research
should
conducted
regarding
ethical
factors,
increasing
standards
usage
administration,
exploring
cooperation
practitioners
engineers
respect
application
practice.
Proposed
solutions,
therefore,
include
enhancing
functions
guaranteeing
policy
instruments
favorable
use
health.
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 263 - 282
Опубликована: Март 13, 2025
Mental
health
care
is
increasingly
integrating
AI
and
deep
learning
for
diagnosing,
treating,
monitoring
patients.
Traditional
assessments
rely
on
subjective
reports,
but
AI-powered
tools
analyze
speech,
facial
expressions,
physiological
signals
objective
insights.
These
innovations
enable
early
detection
of
disorders
like
depression
anxiety.
This
paper
explores
AI's
role
in
diagnostics,
chatbot
therapy,
predictive
analytics
while
addressing
ethical
concerns
bias,
privacy,
patient
autonomy.
Emerging
technologies,
such
as
brain-computer
interfaces
quantum
AI,
are
also
discussed,
highlighting
potential
to
make
mental
more
data-driven,
proactive,
inclusive.
Vestnik nevrologii psihiatrii i nejrohirurgii (Bulletin of Neurology Psychiatry and Neurosurgery),
Год журнала:
2025,
Номер
2, С. 141 - 152
Опубликована: Фев. 15, 2025
Cognitive
impairment
is
a
prevalent
and
socially
significant
issue
affecting
large
portion
of
the
human
population.
Traditional
approaches
to
cognitive
rehabilitation
exhibit
inconsistent
limited
effectiveness,
especially
considering
rapid
digitalization
healthcare.
This
paper
explores
potential
digital
technologies
in
individuals
with
dementia
assesses
their
effectiveness
future
development
prospects.
Computer
programs
can
standardize
automate
training,
offering
structured
delivery
system.
Virtual
reality
enable
enhancement
skills
by
simulating
realistic
scenarios
virtual
environment.
Additionally,
chatbots
artificial
intelligence
offer
personalized,
adaptive
approaches,
while
telemedicine
addresses
challenge
providing
access
specialized
neuropsychological
care.
Existing
research
demonstrates
interventions
rehabilitation,
evidence
supporting
several
tools.
However,
there
dearth
studies
this
area,
integration
these
into
clinical
practice
faces
challenges,
including
sustaining
patient
clinician
engagement,
integration,
rigorous
validation
technologies.
Recent
advancements
reality,
robotics,
are
undergoing
active
testing,
application
impairments
holds
promise
for
near
future.
Artificial
intelligence
(AI)
is
being
used
by
an
increasing
number
of
conversational
agents,
sometimes
known
as
chatbots.
In
applications
related
to
health
care,
such
those
that
educate
and
assist
patients
with
chronic
illnesses,
which
are
among
the
main
causes
mortality
in
21st
century,
they
becoming
more
common.
Chatbots
powered
AI
allows
for
frequent
efficient
engagement
these
patients.
This
systematic
review
aimed
examine
traits,
medical
conditions,
architectures
agents
based
on
artificial
specifically
made
illnesses.
We
searched
four
databases
(Scopus,
Web
Science,
PubMed,
Cumulative
Index
Nursing
Allied
Health
Literature
[CINAHL])
search
relevant
studies
using
specific
inclusion
exclusion
criteria.
Among
databases,
we
found
386
were
screened
duplicates
then
assessed
included
10
most
this
systemic
review.
There
a
dearth
research
AI-based
interactive
what
little
available
primarily
quasi-experimental
studies,
including
chatbots
prototype
stages
employ
natural
language
processing
(NLP)
enable
multimodal
user
engagement.
Future
could
benefit
from
comparing
evaluating
bots
within
between
various
disorders
evidence-based
methodology.
addition
improving
comparability,
structured
development
standardized
evaluation
procedures
improve
caliber
created
certain
diseases
their
subsequent
effects
target
Journal of Primary Care & Community Health,
Год журнала:
2025,
Номер
16
Опубликована: Март 1, 2025
Primary
Health
Care
(PHC)
is
the
cornerstone
of
global
health
care
system
and
primary
objective
for
achieving
universal
coverage.
China’s
PHC
faces
several
challenges,
including
uneven
distribution
medical
resources,
a
lack
qualified
healthcare
personnel,
an
ineffective
implementation
hierarchical
treatment,
serious
situation
regarding
prevention
control
chronic
diseases.
The
rapid
advancement
artificial
intelligence
(AI)
technology,
large
language
models
(LLMs)
demonstrate
significant
potential
in
field
with
their
powerful
natural
processing
reasoning
capabilities,
especially
PHC.
This
review
focuses
on
various
applications
LLMs
PHC,
promotion
disease
prevention,
consultation
management,
diagnosis
triage,
mental
support.
Additionally,
pragmatic
obstacles
were
analyzed,
such
as
transparency,
outcomes
misrepresentation,
privacy
concerns,
social
biases.
Future
development
should
emphasize
interdisciplinary
collaboration
resource
sharing,
ongoing
improvements
equity,
innovative
advancements
models.
There
demand
to
establish
safe,
effective,
equitable,
flexible
ethical
legal
framework,
along
robust
accountability
mechanism,
support
achievement
Frontiers in Neurology,
Год журнала:
2025,
Номер
16
Опубликована: Апрель 4, 2025
Background
Existing
rehabilitation
techniques
are
not
satisfactory
in
improving
motor
function
after
stroke,
resulting
heavy
social
burdens.
With
discovery
of
mirror
neuron
system
(MNS),
action
observation
(AO)
has
become
a
promising
strategy
to
promote
learning
rehabilitation.
Based
on
MNS
theory
and
virtual
reality
(VR)
technology,
we
designed
an
innovative
rehabilitative
approach:
synchronous
360°
VR
video
AO
(VRAO)
neuromuscular
electrical
stimulation
(NMES).
We
hypothesized
that
VRAO+NMES
could
enhance
activation,
thus
improve
upper
limb
activities
daily
living
stroke
survivors.
Methods
To
explore
the
efficacy
mechanism
VRAO+NMES,
this
single
center,
evaluator
blinded,
prospective,
two
arm
parallel
group
randomized
controlled
trial
with
1:1
allocation
ratio.
The
experiment
will
receive
while
control
landscape
combined
NMES.
Fugl-Meyer
Assessment
for
Upper
Extremity
is
primary
outcome
study,
Brunstrom
Recovery
Stages
Extremity,
Manual
Muscle
Test,
Range
Motion,
Modified
Barthel
Index,
Functional
Independence
Measure
secondary
outcomes.
In
addition,
functional
near-infrared
spectroscopy
(fNIRS)
surface
electromyography
(sEMG)
be
used
evaluate
activation
brain
regions
related
muscles,
respectively.
Discussion
Applying
therapy
(AOT)
popular,
another
study
direction
AOT
combine
it
peripheral
stimulations
simultaneously.
Due
its
full
immersive
characteristic
multi-sensory
input,
videos
based
motivation
engagement
level
participants.
fNIRS
sEMG
test
results
may
act
as
good
biomarkers
predict
outcomes,
helping
select
suitable
candidates
new
intervention.
Conclusion
provide
evidence
feasibility
potential
clinical
rehabilitation,
applicability
generalize
use
hospital,
community,
home
settings.
Clinical
registration
https://www.chictr.org.cn/showproj.html?proj=178276
,
Identifier
[ChiCTR2200063552].
Rehabilitación,
Год журнала:
2025,
Номер
59(2), С. 100911 - 100911
Опубликована: Апрель 1, 2025
Artificial
Intelligence
(AI)
is
revolutionizing
rehabilitation
by
enabling
data-driven,
personalized,
and
effective
patient
care.
AI
systems
analyze
patterns,
predict
outcomes,
adapt
treatments
to
individual
needs,
empowering
clinicians
deliver
more
targeted
responsive
interventions.
This
review
explores
AI's
role
in
rehabilitation,
focusing
on
its
applications
personalized
care,
outcome
prediction,
real-time
monitoring.
Evidence
from
current
literature
highlights
how
improves
satisfaction,
engagement,
clinical
outcomes
fostering
a
stronger
therapeutic
alliance
promoting
adherence
treatment
plans.
However,
significant
challenges
remain,
including
data
privacy
concerns,
clinician
training
gaps,
disparities
technology
access.
Addressing
these
barriers
essential
optimize
adoption
fully
realize
potential
enhance
patient-centered
By
integrating
into
daily
practice,
professionals
can
efficient,
individualized,
high-quality
paving
the
way
for
transformative
advancements
field.
