Systematic Reviews,
Год журнала:
2022,
Номер
11(1)
Опубликована: Июнь 17, 2022
Medical
innovations
offer
tremendous
hope.
Yet,
similar
in
governance
(law,
policy,
ethics)
are
likely
necessary
if
society
is
to
realize
medical
innovations'
fruits
and
avoid
their
pitfalls.
As
artificial
intelligence
(AI)
advance
at
a
rapid
pace,
scholars
across
multiple
disciplines
articulating
concerns
health-related
AI
that
require
legal
responses
ensure
the
requisite
balance.
These
scholarly
perspectives
may
provide
critical
insights
into
most
pressing
challenges
will
help
shape
future
regulatory
reforms.
best
of
our
knowledge,
there
no
comprehensive
summary
literature
examining
relation
AI.
We
thus
aim
summarize
map
using
scoping
review
approach.The
framework
developed
by
(J
Soc
Res
Methodol
8:19-32,
2005)
extended
(Implement
Sci
5:69,
2010)
Preferred
Reporting
Items
for
Systematic
Reviews
Meta-Analysis
extension
reviews
(PRISMA-ScR)
guided
protocol
development.
In
close
consultation
with
trained
librarians,
we
develop
highly
sensitive
search
MEDLINE®
(OVID)
adapt
it
databases
designed
comprehensively
capture
texts
law,
medicine,
nursing,
pharmacy,
other
healthcare
professions
(e.g.,
dentistry,
nutrition),
public
health,
computer
science,
engineering.
English-
French-language
records
be
included
they
examine
AI,
describe
or
prioritize
concern
propose
solution
thereto,
were
published
2012
later.
Eligibility
assessment
conducted
independently
duplicate
all
stages.
Coded
data
analyzed
along
themes
stratified
discipline-specific
literatures.This
first-of-its-kind
available
examining,
documenting,
prioritizing
law
policy
reform(s).
The
also
reveal
concerns,
priorities,
proposed
solutions
concerns.
It
thereby
identify
priority
areas
should
focus
reforms
options
stakeholders
reform
processes.This
was
submitted
Open
Science
Foundation
registration
database.
See
https://osf.io/zav7w
.
JMIR Human Factors,
Год журнала:
2024,
Номер
11, С. e47031 - e47031
Опубликована: Янв. 17, 2024
Background
Artificial
intelligence
(AI)–powered
technologies
are
being
increasingly
used
in
almost
all
fields,
including
medicine.
However,
to
successfully
implement
medical
AI
applications,
ensuring
trust
and
acceptance
toward
such
is
crucial
for
their
successful
spread
timely
adoption
worldwide.
Although
applications
medicine
provide
advantages
the
current
health
care
system,
there
also
various
associated
challenges
regarding,
instance,
data
privacy,
accountability,
equity
fairness,
which
could
hinder
application
implementation.
Objective
The
aim
of
this
study
was
identify
factors
related
novel
AI-powered
assess
relevance
those
among
relevant
stakeholders.
Methods
This
a
mixed
methods
design.
First,
rapid
review
existing
literature
conducted,
aiming
Next,
an
electronic
survey
review–derived
disseminated
key
stakeholder
groups.
Participants
(N=22)
were
asked
on
5-point
Likert
scale
(1=irrelevant
5=relevant)
what
extent
they
thought
(N=19)
Results
(N=32
papers)
yielded
110
77
technology
Closely
assigned
1
19
overarching
umbrella
factors,
further
grouped
into
4
categories:
human-related
(ie,
type
institution
professionals
originate
from),
technology-related
explainability
transparency
processes
outcomes),
ethical
legal
use
transparency),
additional
environment
friendly).
categorized
presented
as
statements,
evaluated
by
Survey
participants
represented
researchers
(n=18,
82%),
providers
(n=5,
23%),
hospital
staff
(n=3,
14%),
policy
makers
14%).
Of
16
(84%)
human-related,
technology-related,
legal,
considered
be
high
patient’s
gender,
age,
education
level
found
low
(3/19,
16%).
Conclusions
results
help
implementers
understand
drives
stakeholders
Consequently,
would
allow
strategies
that
facilitate
potential
users.
BMC Medical Ethics,
Год журнала:
2024,
Номер
25(1)
Опубликована: Июнь 22, 2024
In
an
effort
to
improve
the
quality
of
medical
care,
philosophy
patient-centered
care
has
become
integrated
into
almost
every
aspect
community.
Despite
its
widespread
acceptance,
among
patients
and
practitioners,
there
are
concerns
that
rapid
advancements
in
artificial
intelligence
may
threaten
elements
such
as
personal
relationships
with
providers
patient-driven
choices.
This
study
explores
extent
which
confident
comfortable
use
these
technologies
when
it
comes
their
own
individual
identifies
areas
align
or
care.
BMJ,
Год журнала:
2025,
Номер
unknown, С. e081554 - e081554
Опубликована: Фев. 5, 2025
Despite
major
advances
in
artificial
intelligence
(AI)
research
for
healthcare,
the
deployment
and
adoption
of
AI
technologies
remain
limited
clinical
practice.
This
paper
describes
FUTURE-AI
framework,
which
provides
guidance
development
trustworthy
tools
healthcare.
The
Consortium
was
founded
2021
comprises
117
interdisciplinary
experts
from
50
countries
representing
all
continents,
including
scientists,
researchers,
biomedical
ethicists,
social
scientists.
Over
a
two
year
period,
guideline
established
through
consensus
based
on
six
guiding
principles—fairness,
universality,
traceability,
usability,
robustness,
explainability.
To
operationalise
set
30
best
practices
were
defined,
addressing
technical,
clinical,
socioethical,
legal
dimensions.
recommendations
cover
entire
lifecycle
healthcare
AI,
design,
development,
validation
to
regulation,
deployment,
monitoring.
npj Digital Medicine,
Год журнала:
2025,
Номер
8(1)
Опубликована: Янв. 31, 2025
The
confluence
of
new
technologies
with
artificial
intelligence
(AI)
and
machine
learning
(ML)
analytical
techniques
is
rapidly
advancing
the
field
precision
oncology,
promising
to
improve
diagnostic
approaches
therapeutic
strategies
for
patients
cancer.
By
analyzing
multi-dimensional,
multiomic,
spatial
pathology,
radiomic
data,
these
enable
a
deeper
understanding
intricate
molecular
pathways,
aiding
in
identification
critical
nodes
within
tumor's
biology
optimize
treatment
selection.
applications
AI/ML
oncology
are
extensive
include
generation
synthetic
e.g.,
digital
twins,
order
provide
necessary
information
design
or
expedite
conduct
clinical
trials.
Currently,
many
operational
technical
challenges
exist
related
data
technology,
engineering,
storage;
algorithm
development
structures;
quality
quantity
pipeline;
sharing
generalizability;
incorporation
into
current
workflow
reimbursement
models.
Systematic Reviews,
Год журнала:
2022,
Номер
11(1)
Опубликована: Июнь 17, 2022
Medical
innovations
offer
tremendous
hope.
Yet,
similar
in
governance
(law,
policy,
ethics)
are
likely
necessary
if
society
is
to
realize
medical
innovations'
fruits
and
avoid
their
pitfalls.
As
artificial
intelligence
(AI)
advance
at
a
rapid
pace,
scholars
across
multiple
disciplines
articulating
concerns
health-related
AI
that
require
legal
responses
ensure
the
requisite
balance.
These
scholarly
perspectives
may
provide
critical
insights
into
most
pressing
challenges
will
help
shape
future
regulatory
reforms.
best
of
our
knowledge,
there
no
comprehensive
summary
literature
examining
relation
AI.
We
thus
aim
summarize
map
using
scoping
review
approach.The
framework
developed
by
(J
Soc
Res
Methodol
8:19-32,
2005)
extended
(Implement
Sci
5:69,
2010)
Preferred
Reporting
Items
for
Systematic
Reviews
Meta-Analysis
extension
reviews
(PRISMA-ScR)
guided
protocol
development.
In
close
consultation
with
trained
librarians,
we
develop
highly
sensitive
search
MEDLINE®
(OVID)
adapt
it
databases
designed
comprehensively
capture
texts
law,
medicine,
nursing,
pharmacy,
other
healthcare
professions
(e.g.,
dentistry,
nutrition),
public
health,
computer
science,
engineering.
English-
French-language
records
be
included
they
examine
AI,
describe
or
prioritize
concern
propose
solution
thereto,
were
published
2012
later.
Eligibility
assessment
conducted
independently
duplicate
all
stages.
Coded
data
analyzed
along
themes
stratified
discipline-specific
literatures.This
first-of-its-kind
available
examining,
documenting,
prioritizing
law
policy
reform(s).
The
also
reveal
concerns,
priorities,
proposed
solutions
concerns.
It
thereby
identify
priority
areas
should
focus
reforms
options
stakeholders
reform
processes.This
was
submitted
Open
Science
Foundation
registration
database.
See
https://osf.io/zav7w
.
