Frontiers in Artificial Intelligence,
Год журнала:
2024,
Номер
7
Опубликована: Дек. 9, 2024
In
response
to
the
increasing
significance
of
artificial
intelligence
(AI)
in
healthcare,
there
has
been
increased
attention
-
including
a
Presidential
executive
order
create
an
AI
Safety
Institute
potential
threats
posed
by
AI.
While
much
given
conventional
risks
poses
cybersecurity,
and
critical
infrastructure,
here
we
provide
overview
some
unique
challenges
for
medical
community.
Above
beyond
obvious
concerns
about
vetting
algorithms
that
impact
patient
care,
are
additional
subtle
yet
equally
important
things
consider:
harm
its
own
integrity
broader
information
ecosystem.
Recognizing
role
healthcare
professionals
as
both
consumers
contributors
training
data,
this
article
advocates
proactive
approach
understanding
shaping
data
underpins
systems,
emphasizing
need
informed
engagement
maximize
benefits
while
mitigating
risks.
Health care science,
Год журнала:
2024,
Номер
3(5), С. 329 - 349
Опубликована: Окт. 1, 2024
Abstract
The
increasing
integration
of
new
technologies
is
driving
a
fundamental
revolution
in
the
healthcare
sector.
Developments
artificial
intelligence
(AI),
machine
learning,
and
big
data
analytics
have
completely
transformed
diagnosis,
treatment,
care
patients.
AI‐powered
solutions
are
enhancing
efficiency
accuracy
delivery
by
demonstrating
exceptional
skills
personalized
medicine,
early
disease
detection,
predictive
analytics.
Furthermore,
telemedicine
remote
patient
monitoring
systems
overcome
geographical
constraints,
offering
easy
accessible
services,
particularly
underserved
areas.
Wearable
technology,
Internet
Medical
Things,
sensor
empowered
individuals
to
take
an
active
role
tracking
managing
their
health.
These
devices
facilitate
real‐time
collection,
enabling
preventive
care.
Additionally,
development
3D
printing
technology
has
revolutionized
medical
field
production
customized
prosthetics,
implants,
anatomical
models,
significantly
impacting
surgical
planning
treatment
strategies.
Accepting
these
advancements
holds
potential
create
more
patient‐centered,
efficient
system
that
emphasizes
individualized
care,
better
overall
health
outcomes.
This
review's
novelty
lies
exploring
how
radically
transforming
industry,
paving
way
for
effective
all.
It
highlights
capacity
modern
revolutionize
addressing
long‐standing
challenges
improving
Although
approval
use
digital
advanced
analysis
face
scientific
regulatory
obstacles,
they
translational
research.
as
continue
evolve,
poised
alter
environment,
sustainable,
efficient,
ecosystem
future
generations.
Innovation
across
multiple
fronts
will
shape
revolutionizing
provision
healthcare,
outcomes,
equipping
both
patients
professionals
with
tools
make
decisions
receive
treatment.
As
develop
become
integrated
into
standard
practices,
probably
be
accessible,
effective,
than
ever
before.
Internet of Things,
Год журнала:
2024,
Номер
27, С. 101291 - 101291
Опубликована: Июль 20, 2024
In
February
2024,
the
Council
and
European
Parliament
(EP)
agreed
on
Artificial
Intelligence
Regulation
(usually
known
as
AI
Act,
AIA)
.2
This
regulation
evaluates
applications
to
ensure
they
are
used
ethically
responsibly,
promoting
development
of
safe
lawful
across
EU's
single
market.
It
establishes
a
comprehensive
legal
framework
with
risk-based
approach,
aiming
achieve
balance
between
protecting
health,
safety,
fundamental
rights
citizens
ensuring
that
growing
industry
in
Europe
remains
competitive
continues
innovate.
The
AIA
also
includes
governance
mechanisms
oriented
towards
achieving
effective
implementation
throughout
EU.
For
this
purpose,
Office
has
already
been
established.
accordance
provisions
forthcoming
AIA,
it
will
establish
Board,
an
advisory
forum,
scientific
panel.
Furthermore,
be
set
up
at
national
level
so-called
competent
authorities.
way,
system
for
is
emerging,
inspired
by
collaborative
governance,
which
essential
fair
regulations
main
objective
text
critically
examine
established
AIA.
Using
contents
current
version
(April
2024),
analysis
delves
into
structures
designed
implement
As
conclusion,
offers
critical
perspective
highlighting
its
strengths
potential
areas
improvement.
Bioengineering & Translational Medicine,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 9, 2025
Abstract
This
comprehensive
review
explores
the
implications
of
artificial
intelligence
(AI)
in
addressing
cochlear
implant
(CI)
issues
and
revolutionizing
landscape
auditory
prosthetics.
It
begins
with
an
overview
ear
anatomy
hearing
loss,
then
a
CI
technology
its
current
challenges.
The
emphasizes
how
advanced
AI
algorithms
data‐driven
approaches
enhance
adaptability
functionality,
enabling
personalized
rehabilitation
strategies
improving
speech
enhancement.
highlights
diverse
applications
rehabilitation,
including
real‐time
adaptive
control
mechanisms
cognitive
assistants
that
help
users
manage
their
health.
By
outlining
innovative
pathways
future
directions
for
AI‐enhanced
CIs,
paper
sets
stage
transformative
shift
prosthetics,
aiming
to
improve
quality
life
individuals
loss.
Indian Journal of Anaesthesia,
Год журнала:
2025,
Номер
69(1), С. 6 - 9
Опубликована: Янв. 1, 2025
At
the
outset,
whole
Editorial
Board
Team
of
Indian
Journal
Anaesthesia
(IJA)
wishes
everyone
a
very
happy
new
year.
This
special
themed
issue
IJA
presents
various
systematic
reviews
and
meta-analyses
(SRMAs)
on
important
clinically
relevant
topics
narrative
conceptualising
different
aspects
SRMAs.
While
finalising
this
January
2025-themed
IJA,
I
was
thinking
about
what's
next
in
Yes,
we
agree
that
SRMAs,
with
their
robust
methodology,
provide
highest-level
evidence
are
thus
useful
for
bringing
change
our
clinical
practice,
but
three
core
pillars
'evidence-based
medicine'
integrated
into
conclusions
these
SRMAs?
SRMAs
use
high-quality
research
to
synthesise
results
culminate
comprehensive
conclusion
guide
practice.[1-3]
With
better
understanding
availability
advanced
statistical
tools,
increasingly
being
published.
The
not
'just
SRMA';
SRMA
trial
sequential
analysis
(TSA),
pooled
analysis,
network
meta-analysis
(NMA),
individual
participant
data
(IPD)
meta-analysis,
etc.,
also
In
future,
role
artificial
intelligence
(AI)
may
be
underscored.
recent
times,
traditional
concept
involving
pooling
from
published
reach
has
been
challenged
real-world
scenarios.
is
primarily
because
many
limitations
applicability
SRMAs'
conclusions.
Emerging
concepts,
technologies,
strategies,
drugs,
tools
require
updating
Various
analytical
techniques
used
multiple
studies
own
advantages
[Table
1].[1-10]Table
1:
Meta-Analytical
MethodsThe
gadgets,
drugs
limits
conventional
definite
conclusion,
comparing
only
few
them
rather
than
all.
where
NMA
role,
create
hierarchy
therapeutic/management/selection
options.
Even
using
strategy
work
full
extent
as,
at
have
criteria
inclusion
exclusion.
needs
IPD
raw
participant-level
sought
study
authors,
conducted
enable
personalised
subgroup
analyses.
Is
stated
conclusive?
it
sufficiently
powered
conclude?
What
risk
random
errors
false-positive
findings?
Herein,
need
TSA
emphasised.
ensures
futility
or
further
studies.
EVIDENCE-BASED
MEDICINE
(EBM)
AND
high-level
evidence,
imperative
integrate
evidence-based
medicine—best
expertise,
patient
values—to
ensure
patient-centred
care
2].[10]Table
2:
Integrating
Pillars
Evidence-Based
MedicineIt
emphasised
medicine
existing
challenges
implementations
addressed
through
It
time
methodologists
researchers
incorporate
actively
engage
medicine,
ensuring
remain
patient-centred.
ARTIFICIAL
INTELLIGENCE
evolution
AI
its
medical
sciences,
reporting.[11,12]
However,
concerns
limitations,
involvement
considered
due
diligence.
features,
such
as
algorithm-based
automated
literature
search
natural
language
processing
extraction
synthesis,
exploration.
Predictive
modelling
can
identify
gaps
future
trials.
addition,
explored
emerges,
creating
'living
reviews'.
FUTURE
DIRECTIONS
FOR
Preferred
Reporting
Items
Systematic
Reviews
Meta-Analyses
(PRISMA)
guidelines
clear,
transparent,
complete
reporting
Not
focus
more
outcomes,
including
functional
recovery,
quality
life,
patient/caregiver
satisfaction,
return
intended
oncological
management
3].Table
3:
Future
SRMAsIt
hour
match
priorities
priorities.
Continuing
parlance
multidisciplinary
approach,
needed
multi-
cross-disciplinary
involvements.
BMJ Medicine,
Год журнала:
2025,
Номер
4(1), С. e001394 - e001394
Опубликована: Апрель 1, 2025
This
paper
guides
readers
through
the
critical
appraisal
of
a
that
includes
use
artificial
intelligence
(AI)
in
clinical
settings
for
healthcare
delivery.
A
brief
introduction
to
different
types
AI
used
is
given,
along
with
some
ethical
principles
guide
systems
into
healthcare.
Existing
publication
guidelines
studies
are
highlighted.
Ten
preliminary
questions
ask
about
describing
an
based
decision
support
algorithm
suggested.
Italian Journal of Medicine,
Год журнала:
2024,
Номер
18(2)
Опубликована: Апрель 15, 2024
In
hospital
settings,
effective
risk
management
is
critical
to
ensuring
patient
safety,
regulatory
compliance,
and
operational
effectiveness.
Conventional
approaches
assessment
mitigation
frequently
rely
on
manual
procedures
retroactive
analysis,
which
might
not
be
sufficient
recognize
respond
new
risks
as
they
arise.
This
study
examines
how
artificial
intelligence
(AI)
technologies
can
improve
in
healthcare
facilities,
fortifying
safety
precautions
guidelines
while
improving
the
standard
of
care
overall.
Hospitals
proactively
identify
mitigate
risks,
optimize
resource
allocation,
clinical
outcomes
by
utilizing
AI-driven
predictive
analytics,
natural
language
processing,
machine
learning
algorithms.
The
different
applications
AI
are
discussed
this
paper,
along
with
opportunities,
problems,
suggestions
for
their
use
settings.
