Biomedicines,
Год журнала:
2024,
Номер
12(6), С. 1220 - 1220
Опубликована: Май 30, 2024
The
dawn
of
Artificial
intelligence
(AI)
in
healthcare
stands
as
a
milestone
medical
innovation.
Different
fields
are
heavily
involved,
and
pediatric
emergency
medicine
is
no
exception.
We
conducted
narrative
review
structured
two
parts.
first
part
explores
the
theoretical
principles
AI,
providing
all
necessary
background
to
feel
confident
with
these
new
state-of-the-art
tools.
second
presents
an
informative
analysis
AI
models
emergencies.
examined
PubMed
Cochrane
Library
from
inception
up
April
2024.
Key
applications
include
triage
optimization,
predictive
for
traumatic
brain
injury
assessment,
computerized
sepsis
prediction
systems.
In
each
domains,
outperformed
standard
methods.
main
barriers
widespread
adoption
technological
challenges,
but
also
ethical
issues,
age-related
differences
data
interpretation,
paucity
comprehensive
datasets
context.
Future
feasible
research
directions
should
address
validation
through
prospective
more
numerous
sample
sizes
patients.
Furthermore,
our
shows
that
it
essential
tailor
algorithms
specific
needs.
This
requires
close
partnership
between
clinicians
developers.
Building
shared
knowledge
platform
therefore
key
step.
ACM Computing Surveys,
Год журнала:
2024,
Номер
56(8), С. 1 - 36
Опубликована: Март 28, 2024
The
Metaverse,
positioned
as
the
next
frontier
of
Internet,
has
ambition
to
forge
a
virtual
shared
realm
characterized
by
immersion,
hyper-spatiotemporal
dynamics,
and
self-sustainability.
Recent
technological
strides
in
AI,
Extended
Reality,
6G,
blockchain
propel
Metaverse
closer
realization,
gradually
transforming
it
from
science
fiction
into
an
imminent
reality.
Nevertheless,
extensive
deployment
faces
substantial
obstacles,
primarily
stemming
its
potential
infringe
on
privacy
be
susceptible
security
breaches,
whether
inherent
underlying
technologies
or
arising
evolving
digital
landscape.
provisioning
is
poised
confront
various
foundational
challenges
owing
distinctive
attributes,
encompassing
immersive
realism,
hyper-spatiotemporally,
sustainability,
heterogeneity.
This
article
undertakes
comprehensive
study
facing
leveraging
machine
learning
models
for
this
purpose.
In
particular,
our
focus
centers
innovative
distributed
architecture
interactions
across
3D
worlds.
Subsequently,
we
conduct
thorough
review
existing
cutting-edge
measures
designed
systems
while
also
delving
discourse
surrounding
threats.
As
contemplate
future
systems,
outline
directions
open
research
pursuits
Heliyon,
Год журнала:
2024,
Номер
10(7), С. e28778 - e28778
Опубликована: Апрель 1, 2024
This
research
aims
to
find
out
the
factors
affecting
adoption
of
Metaverse
in
healthcare.
study
explores
effect
perceived
ease
use,
usefulness,
and
trust
on
adopting
healthcare
by
keeping
digital
division
metaculture
as
moderating
variables.
The
philosophical
foundation
is
rooted
positivism
paradigm,
methodology
quantitative,
approach
used
deductive.
Data
was
collected
Pakistan
China
through
judgmental
sampling
from
384
respondents.
Partial
Least
Square
Structural
Equation
Modelling
(PLS-SEM)
analyze
data.
findings
validate
relationship
between
use
metaverse
with
β-value
0.236,
t-value
5.207
p-value
0.000,
usefulness
0.233,
4.017
a
0.192,
3.589
0.000.
Results
also
show
that
divide
moderates
relation
having
0.078,
1.848
0.032.
Similarly,
does
not
moderate
relationships
metaverse.
Moreover,
meta
culture
contributes
theoretical
examining
various
necessary
for
its
development.
It
provides
guidelines
developers
adopters
suitable
technology.
Biomedicines,
Год журнала:
2024,
Номер
12(6), С. 1220 - 1220
Опубликована: Май 30, 2024
The
dawn
of
Artificial
intelligence
(AI)
in
healthcare
stands
as
a
milestone
medical
innovation.
Different
fields
are
heavily
involved,
and
pediatric
emergency
medicine
is
no
exception.
We
conducted
narrative
review
structured
two
parts.
first
part
explores
the
theoretical
principles
AI,
providing
all
necessary
background
to
feel
confident
with
these
new
state-of-the-art
tools.
second
presents
an
informative
analysis
AI
models
emergencies.
examined
PubMed
Cochrane
Library
from
inception
up
April
2024.
Key
applications
include
triage
optimization,
predictive
for
traumatic
brain
injury
assessment,
computerized
sepsis
prediction
systems.
In
each
domains,
outperformed
standard
methods.
main
barriers
widespread
adoption
technological
challenges,
but
also
ethical
issues,
age-related
differences
data
interpretation,
paucity
comprehensive
datasets
context.
Future
feasible
research
directions
should
address
validation
through
prospective
more
numerous
sample
sizes
patients.
Furthermore,
our
shows
that
it
essential
tailor
algorithms
specific
needs.
This
requires
close
partnership
between
clinicians
developers.
Building
shared
knowledge
platform
therefore
key
step.
