JMIR AI,
Год журнала:
2023,
Номер
2, С. e40973 - e40973
Опубликована: Март 2, 2023
Background
As
new
technologies
emerge,
there
is
a
significant
shift
in
the
way
care
delivered
on
global
scale.
Artificial
intelligence
(AI)
have
been
rapidly
and
inexorably
used
to
optimize
patient
outcomes,
reduce
health
system
costs,
improve
workflow
efficiency,
enhance
population
health.
Despite
widespread
adoption
of
AI
technologies,
literature
engagement
their
perspectives
how
will
affect
clinical
scarce.
Minimal
can
limit
optimization
these
novel
contribute
suboptimal
use
settings.
Objective
We
aimed
explore
patients’
views
what
skills
they
believe
professionals
should
preparation
for
this
AI-enabled
future
we
better
engage
patients
when
adopting
deploying
Methods
Semistructured
interviews
were
conducted
from
August
2020
December
2021
with
12
individuals
who
any
Canadian
setting.
Interviews
until
thematic
saturation
occurred.
A
analysis
approach
outlined
by
Braun
Clarke
was
inductively
analyze
data
identify
overarching
themes.
Results
Among
interviewed,
8
(67%)
urban
settings
4
(33%)
rural
majority
participants
very
comfortable
technology
(n=6,
50%)
somewhat
familiar
(n=7,
58%).
In
total,
3
themes
emerged:
cultivating
trust,
fostering
engagement,
establishing
governance
validation
technologies.
Conclusions
With
rapid
surge
solutions,
critical
need
understand
values
advancing
quality
contributing
an
equitable
system.
Our
study
demonstrated
that
play
synergetic
role
digital
Patient
vital
addressing
underlying
inequities
optimal
experience.
Future
research
warranted
capture
diverse
various
racial,
ethnic,
socioeconomic
backgrounds.
Digital Health,
Год журнала:
2022,
Номер
8, С. 205520762211167 - 205520762211167
Опубликована: Янв. 1, 2022
Objective
The
attitudes
about
the
usage
of
artificial
intelligence
in
healthcare
are
controversial.
Unlike
perception
professionals,
patients
and
their
companions
have
been
less
interest
so
far.
In
this
study,
we
aimed
to
investigate
among
highly
relevant
group
along
with
influence
digital
affinity
sociodemographic
factors.
Methods
We
conducted
a
cross-sectional
study
using
paper-based
questionnaire
at
German
tertiary
referral
hospital
from
December
2019
February
2020.
consisted
three
sections
examining
(a)
respondents’
technical
affinity,
(b)
different
aspects
(c)
characteristics.
Results
From
total
452
participants,
more
than
90%
already
read
or
heard
intelligence,
but
only
24%
reported
good
expert
knowledge.
Asked
on
general
perception,
53.18%
respondents
rated
use
medicine
as
positive
very
positive,
4.77%
negative
negative.
denied
concerns
strongly
agreed
that
must
be
controlled
by
physician.
Older
patients,
women,
persons
lower
education
were
cautious
healthcare-related
usage.
Conclusions
open
towards
healthcare.
Although
showing
mediocre
knowledge
majority
positive.
Particularly,
insist
physician
supervises
keeps
ultimate
responsibility
for
diagnosis
therapy.
Frontiers in Psychology,
Год журнала:
2023,
Номер
13
Опубликована: Янв. 17, 2023
Advances
in
artificial
intelligence
(AI)
technologies,
together
with
the
availability
of
big
data
society,
creates
uncertainties
about
how
these
developments
will
affect
healthcare
systems
worldwide.
Compassion
is
essential
for
high-quality
and
research
shows
prosocial
caring
behaviors
benefit
human
health
societies.
However,
possible
association
between
AI
technologies
compassion
under
conceptualized
underexplored.The
aim
this
scoping
review
to
provide
a
comprehensive
depth
balanced
perspective
emerging
topic
compassion,
inform
future
practice.
The
questions
were:
How
discussed
relation
healthcare?
are
being
used
enhance
What
gaps
current
knowledge
unexplored
potential?
key
areas
where
could
support
healthcare?A
systematic
following
five
steps
Joanna
Briggs
Institute
methodology.
Presentation
conforms
PRISMA-ScR
(Preferred
Reporting
Items
Systematic
reviews
Meta-Analyses
extension
Scoping
Reviews).
Eligibility
criteria
were
defined
according
3
concept
constructs
(AI
healthcare)
developed
from
literature
informed
by
medical
subject
headings
(MeSH)
words
electronic
searches.
Sources
evidence
Web
Science
PubMed
databases,
articles
published
English
language
2011-2022.
Articles
screened
title/abstract
using
inclusion/exclusion
criteria.
Data
extracted
(author,
date
publication,
type
article,
aim/context
healthcare,
relevant
findings,
country)
was
charted
tables.
Thematic
analysis
an
inductive-deductive
approach
generate
code
categories
data.
A
multidisciplinary
team
assessed
themes
resonance
relevance
practice.Searches
identified
3,124
articles.
total
197
included
after
screening.
number
has
increased
over
10
years
(2011,
n
=
1
2021,
47
Jan-Aug
2022
35
articles).
Overarching
related
(1)
Developments
debates
(7
themes)
Concerns
ethics,
jobs,
loss
empathy;
Human-centered
design
healthcare;
Optimistic
speculation
address
care
gaps;
Interrogation
what
it
means
be
care;
Recognition
potential
patient
monitoring,
virtual
proximity,
access
Calls
curricula
development
professional
education;
Implementation
applications
wellbeing
workforce.
(2)
(10
Empathetic
awareness;
response
relational
behavior;
Communication
skills;
Health
coaching;
Therapeutic
interventions;
Moral
learning;
Clinical
clinical
assessment;
Healthcare
quality
bond
therapeutic
alliance;
Providing
information
advice.
(3)
Gaps
(4
Educational
effectiveness
AI-assisted
Patient
diversity
technologies;
education
practice
settings;
Safety
technologies.
(4)
Key
(3
Enriching
education,
learning
practice;
Extending
healing
spaces;
Enhancing
relationships.There
interest
grown
internationally
last
decade.
In
range
contexts,
empathetic
communication
moral
findings
reconceptualization
as
human-AI
system
intelligent
comprising
six
elements:
Awareness
suffering
(e.g.,
pain,
distress,
risk,
disadvantage);
Understanding
(significance,
context,
rights,
responsibilities
etc.);
Connecting
verbal,
physical,
signs
symbols);
Making
judgment
(the
need
act);
(5)
Responding
intention
alleviate
suffering;
(6)
Attention
effect
outcomes
response.
These
elements
can
operate
at
individual
(human
or
machine)
collective
level
(healthcare
organizations
systems)
cyclical
different
types
suffering.
New
novel
approaches
enrich
learning,
extend
relationships.In
complex
adaptive
such
implemented,
not
ideology,
but
through
strategic
choices,
incentives,
regulation,
training,
well
joined
up
thinking
caring.
Research
funders
encourage
into
Educators,
technologists,
professionals
themselves
Background
Artificial
intelligence
(AI)
technologies
are
transforming
medicine
and
healthcare.
Scholars
practitioners
have
debated
the
philosophical,
ethical,
legal,
regulatory
implications
of
medical
AI,
empirical
research
on
stakeholders’
knowledge,
attitude,
practices
has
started
to
emerge.
This
study
is
a
systematic
review
published
studies
AI
ethics
with
goal
mapping
main
approaches,
findings,
limitations
scholarship
inform
future
practice
considerations.
Methods
We
searched
seven
databases
for
peer-reviewed
evaluated
them
in
terms
types
studied,
geographic
locations,
stakeholders
involved,
methods
used,
ethical
principles
major
findings.
Findings
Thirty-six
were
included
(published
2013-2022).
They
typically
belonged
one
three
topics:
exploratory
stakeholder
knowledge
attitude
toward
theory-building
testing
hypotheses
regarding
factors
contributing
acceptance
identifying
correcting
bias
AI.
Interpretation
There
disconnect
between
high-level
guidelines
developed
by
ethicists
topic
need
embed
tandem
developers,
clinicians,
patients,
scholars
innovation
technology
adoption
studying
ethics.
Medical Science Educator,
Год журнала:
2023,
Номер
33(4), С. 1007 - 1012
Опубликована: Июнь 7, 2023
Abstract
The
increasing
use
of
artificial
intelligence
(AI)
in
medicine
is
associated
with
new
ethical
challenges
and
responsibilities.
However,
special
considerations
concerns
should
be
addressed
when
integrating
AI
applications
into
medical
education,
where
healthcare,
AI,
education
ethics
collide.
This
commentary
explores
the
biomedical
responsibilities
institutions
incorporating
by
identifying
potential
limitations,
goal
implementing
applicable
recommendations.
recommendations
presented
are
intended
to
assist
developing
institutional
guidelines
for
educators
students.
IEEE Access,
Год журнала:
2024,
Номер
12, С. 31014 - 31035
Опубликована: Янв. 1, 2024
In
the
past
decade,
deployment
of
deep
learning
(Artificial
Intelligence
(AI))
methods
has
become
pervasive
across
a
spectrum
real-world
applications,
often
in
safety-critical
contexts.
This
comprehensive
research
article
rigorously
investigates
ethical
dimensions
intricately
linked
to
rapid
evolution
AI
technologies,
with
particular
focus
on
healthcare
domain.
Delving
deeply,
it
explores
multitude
facets
including
transparency,
adept
data
management,
human
oversight,
educational
imperatives,
and
international
collaboration
within
realm
advancement.
Central
this
is
proposition
conscientious
framework,
meticulously
crafted
accentuate
values
equity,
answerability,
human-centric
orientation.
The
second
contribution
in-depth
thorough
discussion
limitations
inherent
systems.
It
astutely
identifies
potential
biases
intricate
challenges
navigating
multifaceted
Lastly,
unequivocally
accentuates
pressing
need
for
globally
standardized
ethics
principles
frameworks.
Simultaneously,
aptly
illustrates
adaptability
framework
proposed
herein,
positioned
skillfully
surmount
emergent
challenges.
Integrative Medicine Research,
Год журнала:
2024,
Номер
13(1), С. 101024 - 101024
Опубликована: Фев. 9, 2024
The
convergence
of
traditional,
complementary,
and
integrative
medicine
(TCIM)
with
artificial
intelligence
(AI)
is
a
promising
frontier
in
healthcare.
TCIM
patient-centric
approach
that
combines
conventional
complementary
therapies,
emphasizing
holistic
well-being.
AI
can
revolutionize
healthcare
through
data-driven
decision-making
personalized
treatment
plans.
This
article
explores
how
technologies
complement
enhance
TCIM,
aligning
the
shared
objectives
researchers
from
both
fields
improving
patient
outcomes,
enhancing
care
quality,
promoting
wellness.
integration
introduces
exciting
opportunities
but
also
noteworthy
challenges.
may
augment
by
assisting
early
disease
detection,
providing
plans,
predicting
health
trends,
engagement.
Challenges
at
intersection
include
data
privacy
security,
regulatory
complexities,
maintaining
human
touch
patient-provider
relationships,
mitigating
bias
algorithms.
Patients'
trust,
informed
consent,
legal
accountability
are
all
essential
considerations.
Future
directions
AI-enhanced
advanced
medicine,
understanding
efficacy
herbal
remedies,
studying
interactions.
Research
on
mitigation,
acceptance,
trust
AI-driven
crucial.
In
this
article,
we
outlined
merging
holds
great
promise
delivery,
personalizing
preventive
care,
Addressing
challenges
fostering
collaboration
between
experts,
practitioners,
policymakers,
however,
vital
to
harnessing
full
potential
integration.
Journal of patient-centered research and reviews,
Год журнала:
2024,
Номер
11(1), С. 51 - 62
Опубликована: Апрель 2, 2024
Artificial
intelligence
(AI)
technology
is
being
rapidly
adopted
into
many
different
branches
of
medicine.
Although
research
has
started
to
highlight
the
impact
AI
on
health
care,
focus
patient
perspectives
scarce.
This
scoping
review
aimed
explore
literature
adult
patients'
use
an
array
technologies
in
care
setting
for
design
and
deployment.
Diagnostics,
Год журнала:
2023,
Номер
13(13), С. 2308 - 2308
Опубликована: Июль 7, 2023
Artificial
intelligence
is
highly
regarded
as
the
most
promising
future
technology
that
will
have
a
great
impact
on
healthcare
across
all
specialties.
Its
subsets,
machine
learning,
deep
and
artificial
neural
networks,
are
able
to
automatically
learn
from
massive
amounts
of
data
can
improve
prediction
algorithms
enhance
their
performance.
This
area
still
under
development,
but
latest
evidence
shows
potential
in
diagnosis,
prognosis,
treatment
urological
diseases,
including
bladder
cancer,
which
currently
using
old
tools
historical
nomograms.
review
focuses
significant
comprehensive
literature
management
cancer
investigates
near
introduction
clinical
practice.
