PeerJ,
Journal Year:
2024,
Volume and Issue:
12, P. e18391 - e18391
Published: Nov. 4, 2024
Plasma
cell
dyscrasias
encompass
a
diverse
set
of
disorders,
where
early
and
precise
diagnosis
is
essential
for
optimizing
patient
outcomes.
Despite
advancements,
current
diagnostic
methodologies
remain
underutilized
in
applying
artificial
intelligence
(AI)
to
routine
laboratory
data.
This
study
seeks
construct
an
AI-driven
model
leveraging
standard
parameters
enhance
accuracy
classification
efficiency
plasma
dyscrasias.
BMC Medical Informatics and Decision Making,
Journal Year:
2025,
Volume and Issue:
25(1)
Published: Feb. 5, 2025
Abstract
Background
Artificial
intelligence
(AI)-based
systems
are
being
rapidly
integrated
into
the
fields
of
health
and
social
care.
Although
such
can
substantially
improve
provision
care,
diverse
marginalized
populations
often
incorrectly
or
insufficiently
represented
within
these
systems.
This
review
aims
to
assess
influence
AI
on
care
among
populations,
particularly
with
regard
issues
related
inclusivity
regulatory
concerns.
Methods
We
followed
Preferred
Reporting
Items
for
Systematic
Reviews
Meta-Analyses
guidelines.
Six
leading
databases
were
searched,
129
articles
selected
this
in
line
predefined
eligibility
criteria.
Results
research
revealed
disparities
outcomes,
accessibility,
representation
groups
due
biased
data
sources
a
lack
training
datasets,
which
potentially
exacerbate
inequalities
delivery
communities.
Conclusion
development
practices,
legal
frameworks,
policies
must
be
reformulated
ensure
that
is
applied
an
equitable
manner.
A
holistic
approach
used
address
disparities,
enforce
effective
regulations,
safeguard
privacy,
promote
inclusion
equity,
emphasize
rigorous
validation.
Journal of Medical Internet Research,
Journal Year:
2025,
Volume and Issue:
27, P. e52244 - e52244
Published: March 6, 2025
Data
on
the
social
determinants
of
health
could
be
used
to
improve
care,
support
quality
improvement
initiatives,
and
track
progress
toward
equity.
However,
this
data
collection
is
not
widespread.
Artificial
intelligence
(AI),
specifically
natural
language
processing
machine
learning,
derive
from
electronic
medical
records.
This
reduce
time
resources
required
obtain
data.
study
aimed
understand
perspectives
a
diverse
sample
Canadians
use
AI
information
record
data,
including
benefits
concerns.
Using
qualitative
description
approach,
in-depth
interviews
were
conducted
with
195
participants
purposefully
recruited
Ontario,
Newfoundland
Labrador,
Manitoba,
Saskatchewan.
Transcripts
analyzed
using
an
inductive
deductive
content
analysis.
A
total
4
themes
identified.
First,
was
described
as
inevitable
future,
facilitating
more
efficient,
accessible
in
primary
care.
Second,
expressed
concerns
about
potential
care
harms
distrust
public
systems.
Third,
some
indicated
that
lead
loss
human
touch
emphasizing
preference
for
strong
relationships
providers
individualized
Fourth,
critical
importance
consent
need
safeguards
protect
patient
trust.
These
findings
provide
important
considerations
particularly
when
administrators
decision
makers
seek
Health Expectations,
Journal Year:
2025,
Volume and Issue:
28(2)
Published: March 17, 2025
ABSTRACT
Introduction
Artificial
intelligence
(AI)
offers
several
opportunities
to
enhance
medical
care,
but
practical
application
is
limited.
Consideration
of
patient
needs
essential
for
the
successful
implementation
AI‐based
systems.
Few
studies
have
explored
patients'
perceptions,
especially
in
Germany,
resulting
insufficient
exploration
perspectives
outpatients,
older
patients
and
with
chronic
diseases.
We
aimed
explore
how
perceive
AI
focusing
on
relationships
physicians
ethical
aspects.
Methods
conducted
a
qualitative
study
six
semi‐structured
focus
groups
from
June
2022
March
2023.
analysed
data
using
content
analysis
approach
by
systemising
textual
material
via
coding
system.
Participants
were
mostly
recruited
outpatient
settings
regions
Halle
Erlangen,
Germany.
They
enrolled
primarily
through
convenience
sampling
supplemented
purposive
sampling.
Results
Patients
(
N
=
35;
13
females,
22
males)
median
age
50
years
participated.
mixed
socioeconomic
status
affinity
new
technology.
Most
had
Perceived
main
advantages
its
efficient
flawless
functioning,
ability
process
provide
large
volume,
increased
safety.
Major
perceived
disadvantages
impersonality,
potential
security
issues,
fear
errors
based
staff
relying
too
much
AI.
A
dominant
theme
was
that
human
interaction,
personal
conversation,
understanding
emotions
cannot
be
replaced
emphasised
need
involve
everyone
informing
about
considered
as
responsible
decisions
applications.
Transparency
use
protection
other
important
points.
Conclusions
could
generally
imagine
support
care
if
usage
focused
well‐being
relationship
maintained.
Including
development
adequate
communication
systems
are
practice.
Patient
or
Public
Contribution
Patients'
perceptions
participants
this
crucial.
Further,
assessed
presentation
comprehensibility
research
during
pretest,
recommended
adaptations
implemented.
After
each
FG,
space
provided
requesting
modifications
discussion.
Frontiers in Digital Health,
Journal Year:
2025,
Volume and Issue:
7
Published: Jan. 27, 2025
Background
The
growth
of
the
use
artificial
intelligence
(AI)
and
robotic
solutions
in
healthcare
is
accompanied
by
high
expectations
for
improved
efficiency
quality
services.
However,
such
technologies
can
be
a
source
anxiety
patients
whose
experiences
with
technology
differ
from
medical
staff's.
This
study
assessed
attitudes
toward
AI
robots
delivering
health
services
performing
various
tasks
medicine
related
fields
Polish
society.
Methods
50
semistructured
in-depth
interviews
were
conducted
participants
diversified
socio-demographic
profiles.
interviewees
initially
recruited
convenience
sample;
then,
process
was
continued
using
snowballing
technique.
transcribed
analyzed
MAXQDA
Analytics
Pro
2022
program
(release
22.7.0).
An
interpretative
approach
to
qualitative
content
analysis
applied
responses
research
questions.
Results
yielded
three
main
themes:
positive
negative
perceptions
ontological
concerns
about
AI,
which
went
beyond
objections
usefulness
technology.
Positive
associated
overall
higher
trust
technology,
need
adequately
respond
demographic
challenges,
conviction
that
lower
workload
personnel.
Negative
originated
convictions
regarding
unreliability
lack
proper
technological
political
control
over
AI;
an
equally
important
topic
inability
entities
feel
express
emotions.
third
theme
potential
interaction
machines
equipped
human-like
traits
insecurity.
Conclusions
showed
patients'
vary
according
their
recognition
urgent
problems
(staff
workload,
time
diagnosis),
beliefs
reliability
functioning
new
technologies.
Emotional
contact
looking
or
like
humans
are
also
respondents'
attitudes.
Sports,
Journal Year:
2025,
Volume and Issue:
13(4), P. 92 - 92
Published: March 24, 2025
In
this
discussion
paper
based
on
preliminary
data,
the
safety
and
other
quality
criteria
of
ChatGPT-4o-generated
exercise
plans
for
patients
with
type
2
diabetes
mellitus
(T2DM)
are
evaluated.
The
study
team
created
three
fictional
patient
profiles
varying
in
sex,
age,
body
mass
index,
secondary
diseases/complications,
medication,
self-rated
physical
fitness,
weekly
routine
personal
preferences.
Three
distinct
prompts
were
used
to
generate
each
patient.
While
Prompt
1
was
very
simple,
3
included
more
detailed
requests.
optimized
by
ChatGPT
itself.
coaching
experts
reviewed
discussed
their
evaluations.
Some
showed
serious
issues,
especially
diseases/complications.
most
incorporated
key
training
principles,
they
some
deficits,
e.g.,
insufficient
feasibility.
use
(Prompt
3)
tended
result
elaborate
better
ratings.
may
have
issues
T2DM,
indicating
need
consult
a
professional
coach
feedback
before
starting
program.
