Advances in human and social aspects of technology book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 199 - 232
Published: Oct. 18, 2024
The
rise
of
Artificial
Intelligence
(AI)
in
healthcare
has
led
to
significant
advancements
geriatric
nursing,
transforming
both
clinical
outcomes
and
care
delivery.
Yet,
as
AI
plays
an
increasing
role
patient
care,
there
is
growing
recognition
the
need
balance
technological
innovation
with
compassionate,
human-centred
care.
This
chapter
explores
how
emotional
intelligence
(EI)
can
complement
one
another
improve
physical
mental
health
older
adults.
examines
critical
nursing
discusses
support,
rather
than
replace,
empathetic
emotionally
aware
provided
by
nurses.
Through
case
studies,
practical
applications,
theoretical
analysis,
this
illustrates
integrating
EI
enhance
while
maintaining
human
touch
essential
nursing.
Ethical
considerations,
such
dignity
autonomy,
future
AI-driven
world
are
also
explored.
Antibiotics,
Journal Year:
2024,
Volume and Issue:
13(1), P. 77 - 77
Published: Jan. 13, 2024
Healthcare-associated
infections
(HAIs)
pose
significant
challenges
in
healthcare
systems,
with
preventable
surveillance
playing
a
crucial
role.
Traditional
surveillance,
although
effective,
is
resource-intensive.
The
development
of
new
technologies,
such
as
artificial
intelligence
(AI),
can
support
traditional
analysing
an
increasing
amount
health
data
or
meeting
patient
needs.
We
conducted
scoping
review,
following
the
PRISMA-ScR
guideline,
searching
for
studies
digital
technologies
applied
to
control,
and
prevention
HAIs
hospitals
LTCFs
published
from
2018
4
November
2023.
literature
search
yielded
1292
articles.
After
title/abstract
screening
full-text
screening,
43
articles
were
included.
mean
study
duration
was
43.7
months.
Surgical
site
(SSIs)
most-investigated
HAI
machine
learning
most-applied
technology.
Three
main
themes
emerged
thematic
analysis:
empowerment,
workload
reduction
cost
reduction,
improved
sensitivity
personalization.
Comparative
analysis
between
methods
showed
different
population
types,
examining
larger
populations
AI
algorithm
training.
While
tools
show
promise
especially
SSIs,
persist
resource
distribution
interdisciplinary
integration
settings,
highlighting
need
ongoing
implementation
strategies.
The American Journal of Managed Care,
Journal Year:
2024,
Volume and Issue:
30(Spec. No. 6), P. SP445 - SP451
Published: May 30, 2024
To
present
primary
care
physician
(PCP)
suggestions
for
design
and
implementation
of
a
decision
aid
(DA)
tool
to
support
patient-provider
shared
decision-making
on
lung
cancer
screening
(LCS).
Rheumatology & autoimmunity,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 27, 2025
Abstract
Rheumatoid
arthritis
(RA)
is
a
chronic
autoimmune
condition
that
causes
joint
inflammation
and
damage
significantly
affects
patients'
quality
of
life.
Over
the
past
5
years,
application
artificial
intelligence
(AI),
particularly
deep
learning,
has
resulted
in
notable
advancements
field
rheumatology.
This
review
explores
these
developments,
highlighting
how
AI
enhanced
precision
reliability
imaging
techniques,
such
as
radiography,
ultrasound
imaging,
magnetic
resonance
for
managing
RA.
In
addition,
integration
diverse
data
sources,
including
clinical
records,
genetic
profiles,
examinations,
facilitated
more
accurate
predictions
formulation
personalized
treatment
strategies.
However,
challenges
variability,
complexity
models,
ethical
considerations
remain.
Addressing
issues
essential
further
progress.
Future
research
should
focus
on
improving
integration,
model
interpretability,
deployment
practice.
These
have
potential
to
improve
diagnosis
management
RA,
moving
closer
goals
medicine
this
field.
Journal of Evidence-Based Medicine,
Journal Year:
2025,
Volume and Issue:
18(2)
Published: April 2, 2025
The
development
of
artificial
intelligence
(AI)
for
traditional
Chinese
medicine
(TCM)
has
played
an
important
role
in
clinical
decision-making,
mainly
reflected
the
intersectionality
and
variability
symptoms,
syndromes,
patterns
TCM
multiple
diseases
holistic
differentiation
(MDHD).
This
study
aimed
to
develop
a
AI
method
system
decisions
more
transparent
with
explainable
structural
framework.
developed
syndrome
elements
integration
priori
rule
deep
learning
(TCM-SEI-RD)
TCM-MDHD
by
high-quality
expert
knowledge
datasets,
predict
various
syndromes
hierarchical
modules.
TCM-BERT-CNN
model
fused
BERT
CNN
capture
feature-related
sequence,
as
benchmark
TCM-SEI-RD
method,
improve
performance
predicting
elements.
framework
involved
"diseases-syndromes-patterns"
sequences,
provide
distributed
results
credibility.
For
overall
elements,
achieves
95.4%,
94.43%,
94.89%
precision,
recall,
F1
score,
respectively,
3.33%,
2.28%,
2.81%
improvement
over
model.
demonstrates
credibility
grading
at
each
stage
uses
practical
example
illustrate
process
decision-making
transparency
Our
system,
general
technologies
diagnosis
diseases,
can
diagnostic
basis
best
preparations
rational
use,
distribute
interpretability
process.
Sensors,
Journal Year:
2024,
Volume and Issue:
24(11), P. 3491 - 3491
Published: May 28, 2024
In
the
last
few
decades,
there
has
been
an
ongoing
transformation
of
our
healthcare
system
with
larger
use
sensors
for
remote
care
and
artificial
intelligence
(AI)
tools.
particular,
improved
by
new
algorithms
learning
capabilities
have
proven
their
value
better
patient
care.
Sensors
AI
systems
are
no
longer
only
non-autonomous
devices
such
as
ones
used
in
radiology
or
surgical
robots;
novel
tools
a
certain
degree
autonomy
aiming
to
largely
modulate
medical
decision.
Thus,
will
be
situations
which
doctor
is
one
making
decision
final
say
other
cases
might
apply
presented
autonomous
device.
As
those
two
hugely
different
situations,
they
should
not
treated
same
way,
liability
rules
apply.
Despite
real
interest
promise
medicine,
doctors
patients
reluctant
it.
One
important
reason
lack
clear
definition
liability.
Nobody
wants
at
fault,
even
prosecuted,
because
followed
advice
from
system,
notably
when
it
perfectly
adapted
specific
patient.
Fears
present
simple
use,
during
telemedicine
visits
based
on
very
useful,
clinically
pertinent
sensors;
risk
missing
parameter;
and,
course,
appears
“intelligent”,
potentially
replacing
doctors’
judgment.
This
paper
aims
provide
overview
health
professional
context
healthcare,
analyzing
four
regimes:
contract-based
approach,
approach
breach
duty
inform,
fault-based
related
good
itself.
We
also
discuss
future
challenges
opportunities
promising
domain
medicine.
Clinical and Experimental Dental Research,
Journal Year:
2024,
Volume and Issue:
10(4)
Published: July 5, 2024
Abstract
Objectives
With
Artificial
Intelligence
(AI)
profoundly
affecting
education,
ensuring
that
students
in
health
disciplines
are
ready
to
embrace
AI
is
essential
for
their
future
workforce
integration.
This
study
aims
explore
dental
students'
readiness
use
AI,
perceptions
about
education
and
healthcare,
AI‐related
educational
needs.
Material
Methods
A
cross‐sectional
survey
was
conducted
among
at
the
College
of
Dental
Medicine,
Qatar
University.
The
assessed
using
Medical
Readiness
Scale
(MAIRS).
Students'
healthcare
needs
were
also
explored.
Results
total
94
responded
survey.
scores
average
(3.3
±
0.64
out
5);
while
participants
appeared
more
vision
ethics
domains
MAIRS,
they
showed
less
regarding
cognition
ability.
Participants
scored
on
(3.35
0.45
5),
with
concerns
risks
disadvantages.
They
expressed
a
high
need
knowledge
skills
related
(84%),
health‐related
research
(81.9%),
radiology
imaging
procedures
(79.8%).
Student
had
significant
correlation
perceived
level
knowledge.
Conclusions
first
exploring
readiness,
perceptions,
applications
healthcare.
gaps
could
inform
curricular
Advancing
deepening
comprehension
can
empower
professionals
through
anticipated
advances
AI‐driven
landscape.
Hellenic Journal of Cardiology,
Journal Year:
2024,
Volume and Issue:
unknown
Published: July 1, 2024
Advances
in
artificial
intelligence
(AI)
and
machine
learning
systems
promise
faster,
more
efficient,
personalized
care.
While
many
of
these
models
are
built
on
the
premise
improving
access
to
timely
screening,
diagnosis,
treatment
cardiovascular
disease,
their
validity
accessibility
across
diverse
international
cohorts
remain
unknown.
In
this
mini-review
article,
we
summarize
key
obstacles
effort
design
AI
that
will
be
scalable,
accessible,
accurate
distinct
geographical
temporal
settings.
We
discuss
representativeness,
interoperability,
quality
assurance,
importance
vendor-agnostic
data
types
available
end-users
globe.
These
topics
illustrate
how
integration
principles
into
development
is
crucial
maximizing
global
benefits
cardiology.
Frontiers in Medicine,
Journal Year:
2024,
Volume and Issue:
11
Published: Aug. 16, 2024
Robotics
and
artificial
intelligence
have
marked
the
beginning
of
a
new
era
in
care
integration
people
with
disabilities,
helping
to
promote
their
independence,
autonomy
social
participation.
In
this
area,
bioethical
reflection
assumes
key
role
at
anthropological,
ethical,
legal
socio-political
levels.
However,
there
is
currently
substantial
diversity
opinions
ethical
arguments,
as
well
lack
consensus
on
use
assistive
robots,
while
focus
remains
predominantly
usability
products.
The
article
presents
analysis
that
highlights
risk
arising
from
using
embodied
according
functionalist
model.
Failure
recognize
disability
result
complex
interplay
between
health,
personal
situational
factors
could
potential
damage
intrinsic
dignity
person
human
relations
healthcare
workers.
Furthermore,
danger
discrimination
accessing
these
technologies
highlighted,
emphasizing
need
for
an
approach
considers
moral
implications
implementing
AI
field
rehabilitation.
