BMC Medical Education,
Год журнала:
2023,
Номер
23(1)
Опубликована: Сен. 22, 2023
Abstract
Introduction
Healthcare
systems
are
complex
and
challenging
for
all
stakeholders,
but
artificial
intelligence
(AI)
has
transformed
various
fields,
including
healthcare,
with
the
potential
to
improve
patient
care
quality
of
life.
Rapid
AI
advancements
can
revolutionize
healthcare
by
integrating
it
into
clinical
practice.
Reporting
AI’s
role
in
practice
is
crucial
successful
implementation
equipping
providers
essential
knowledge
tools.
Research
Significance
This
review
article
provides
a
comprehensive
up-to-date
overview
current
state
practice,
its
applications
disease
diagnosis,
treatment
recommendations,
engagement.
It
also
discusses
associated
challenges,
covering
ethical
legal
considerations
need
human
expertise.
By
doing
so,
enhances
understanding
significance
supports
organizations
effectively
adopting
technologies.
Materials
Methods
The
investigation
analyzed
use
system
relevant
indexed
literature,
such
as
PubMed/Medline,
Scopus,
EMBASE,
no
time
constraints
limited
articles
published
English.
focused
question
explores
impact
applying
settings
outcomes
this
application.
Results
Integrating
holds
excellent
improving
selection,
laboratory
testing.
tools
leverage
large
datasets
identify
patterns
surpass
performance
several
aspects.
offers
increased
accuracy,
reduced
costs,
savings
while
minimizing
errors.
personalized
medicine,
optimize
medication
dosages,
enhance
population
health
management,
establish
guidelines,
provide
virtual
assistants,
support
mental
care,
education,
influence
patient-physician
trust.
Conclusion
be
used
diagnose
diseases,
develop
plans,
assist
clinicians
decision-making.
Rather
than
simply
automating
tasks,
about
developing
technologies
that
across
settings.
However,
challenges
related
data
privacy,
bias,
expertise
must
addressed
responsible
effective
healthcare.
npj Digital Medicine,
Год журнала:
2023,
Номер
6(1)
Опубликована: Июнь 23, 2023
Chatbots
(also
known
as
conversational
agents
and
virtual
assistants)
offer
the
potential
to
deliver
healthcare
in
an
efficient,
appealing
personalised
manner.
The
purpose
of
this
systematic
review
meta-analysis
was
evaluate
efficacy
chatbot
interventions
designed
improve
physical
activity,
diet
sleep.
Electronic
databases
were
searched
for
randomised
non-randomised
controlled
trials,
pre-post
trials
that
evaluated
targeting
and/or
sleep,
published
before
1
September
2022.
Outcomes
total
steps,
moderate-to-vigorous
activity
(MVPA),
fruit
vegetable
consumption,
sleep
quality
duration.
Standardised
mean
differences
(SMD)
calculated
compare
intervention
effects.
Subgroup
analyses
conducted
assess
type,
duration,
output
use
artificial
intelligence.
Risk
bias
assessed
using
Effective
Public
Health
Practice
Project
Quality
Assessment
tool.
Nineteen
included.
Sample
sizes
ranged
between
25-958,
participant
age
9-71
years.
Most
(n
=
15,
79%)
targeted
most
had
a
low-quality
rating
14,
74%).
Meta-analysis
results
showed
significant
effects
(all
p
<
0.05)
chatbots
increasing
(SMD
0.28
[95%
CI
0.16,
0.40]),
daily
steps
0.17,
0.39]),
MVPA
0.53
0.24,
0.83]),
consumption
0.59
0.25,
0.93]),
duration
0.44
0.32,
0.55])
0.50
0.09,
0.90]).
text-based,
intelligence
more
efficacious
than
speech/voice
multicomponent
chatbot-only
0.05).
Findings
from
indicate
are
quality.
Chatbot
across
range
populations
groups,
with
both
short-
longer-term
interventions,
only
being
efficacious.
Obesity Pillars,
Год журнала:
2023,
Номер
6, С. 100065 - 100065
Опубликована: Апрель 20, 2023
This
Obesity
Medicine
Association
(OMA)
Clinical
Practice
Statement
(CPS)
provides
clinicians
an
overview
of
Artificial
Intelligence,
focused
on
the
management
patients
with
obesity.
Journal of Medical Internet Research,
Год журнала:
2024,
Номер
26, С. e56930 - e56930
Опубликована: Апрель 12, 2024
Background
Chatbots,
or
conversational
agents,
have
emerged
as
significant
tools
in
health
care,
driven
by
advancements
artificial
intelligence
and
digital
technology.
These
programs
are
designed
to
simulate
human
conversations,
addressing
various
care
needs.
However,
no
comprehensive
synthesis
of
chatbots’
roles,
users,
benefits,
limitations
is
available
inform
future
research
application
the
field.
Objective
This
review
aims
describe
characteristics,
focusing
on
their
diverse
roles
pathway,
user
groups,
limitations.
Methods
A
rapid
published
literature
from
2017
2023
was
performed
with
a
search
strategy
developed
collaboration
sciences
librarian
implemented
MEDLINE
Embase
databases.
Primary
studies
reporting
chatbot
benefits
were
included.
Two
reviewers
dual-screened
results.
Extracted
data
subjected
content
analysis.
Results
The
categorized
into
2
themes:
delivery
remote
services,
including
patient
support,
management,
education,
skills
building,
behavior
promotion,
provision
administrative
assistance
providers.
User
groups
spanned
across
patients
chronic
conditions
well
cancer;
individuals
focused
lifestyle
improvements;
demographic
such
women,
families,
older
adults.
Professionals
students
also
alongside
seeking
mental
behavioral
change,
educational
enhancement.
chatbots
classified
improvement
quality
efficiency
cost-effectiveness
delivery.
identified
encompassed
ethical
challenges,
medicolegal
safety
concerns,
technical
difficulties,
experience
issues,
societal
economic
impacts.
Conclusions
Health
offer
wide
spectrum
applications,
potentially
impacting
aspects
care.
While
they
promising
for
improving
quality,
integration
system
must
be
approached
consideration
ensure
optimal,
safe,
equitable
use.
Brain Sciences,
Год журнала:
2025,
Номер
15(1), С. 47 - 47
Опубликована: Янв. 6, 2025
Background/Objectives:
The
evolution
of
digital
technology
enhances
the
broadening
a
person's
intellectual
growth.
Research
points
out
that
implementing
innovative
applications
world
improves
human
social,
cognitive,
and
metacognitive
behavior.
Artificial
intelligence
chatbots
are
yet
another
human-made
construct.
These
forms
software
simulate
conversation,
understand
process
user
input,
provide
personalized
responses.
Executive
function
includes
set
higher
mental
processes
necessary
for
formulating,
planning,
achieving
goal.
present
study
aims
to
investigate
executive
reinforcement
through
artificial
chatbots,
outlining
potentials,
limitations,
future
research
suggestions.
Specifically,
examined
three
questions:
use
conversational
in
functioning
training,
their
impact
on
executive-cognitive
skills,
duration
any
improvements.
Methods:
assessment
existing
literature
was
implemented
using
systematic
review
method,
according
PRISMA
2020
Principles.
avalanche
search
method
employed
conduct
source
following
databases:
Scopus,
Web
Science,
PubMed,
complementary
Google
Scholar.
This
included
studies
from
2021
experimental,
observational,
or
mixed
methods.
It
AI-based
conversationalists
support
functions,
such
as
anxiety,
stress,
depression,
memory,
attention,
cognitive
load,
behavioral
changes.
In
addition,
this
general
populations
with
specific
neurological
conditions,
all
peer-reviewed,
written
English,
full-text
access.
However,
excluded
before
2021,
reviews,
non-AI-based
conversationalists,
not
targeting
range
skills
abilities,
without
open
criteria
aligned
objectives,
ensuring
focus
AI
agents
function.
initial
collection
totaled
n
=
115
articles;
however,
eligibility
requirements
led
final
selection
10
studies.
Results:
findings
suggested
positive
effects
enhance
improve
skills.
Although,
several
limitations
were
identified,
making
it
still
difficult
generalize
reproduce
effects.
Conclusions:
an
tool
can
assistant
learning
expanding
contributing
metacognitive,
social
development
individual.
its
training
is
at
primary
stage.
highlighted
need
unified
framework
reference
studies,
better
designs,
diverse
populations,
larger
sample
sizes
participants,
longitudinal
observe
long-term
use.
Journal of Medical Internet Research,
Год журнала:
2022,
Номер
24(9), С. e40141 - e40141
Опубликована: Сен. 21, 2022
Background:
Evidence
on
the
long-term
effects
of
weight
management
smartphone
apps
various
weight-related
outcomes
remains
scarce.
Objective:
In
this
review,
we
aimed
to
examine
anthropometric,
metabolic,
and
dietary
at
time
points.
Methods:
Articles
published
from
database
inception
March
10,
2022
were
searched,
7
databases
(Embase,
CINAHL,
PubMed,
PsycINFO,
Cochrane
Library,
Scopus,
Web
Science)
using
forward
backward
citation
tracking.
All
randomized
controlled
trials
that
reported
change
as
an
outcome
in
adults
with
overweight
obesity
included.
We
performed
separate
meta-analyses
random
models
for
weight,
waist
circumference,
high-density
lipoprotein
cholesterol,
low-density
blood
glucose
level,
pressure,
total
energy
intake
per
day.
Methodological
quality
was
assessed
Risk
Bias
tool.
Results:
Based
our
meta-analyses,
loss
sustained
between
3
12
months,
a
peak
2.18
kg
months
tapered
down
1.63
months.
did
not
find
significant
benefits
secondary
examined,
except
slight
improvement
systolic
pressure
Most
included
studies
covered
app-based
interventions
comprised
components
beyond
food
logging,
such
real-time
diet
exercise
self-monitoring,
personalized
remote
progress
tracking,
timely
feedback
provision,
smart
devices
synchronized
activity
data
smartphones,
libraries
physical
ideas.
Conclusions:
Smartphone
are
effective
initiating
sustaining
but
their
minimal
current
states.
Future
could
consider
aspects
socioecological
model.
Conversational
dialectic
simulate
health
coaches
be
useful
enhance
user
engagement
effectiveness.
Trial
Registration:
International
Prospective
Register
Systematic
Reviews
(PROSPERO)
CRD42022329197;
https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=329197
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery,
Год журнала:
2023,
Номер
13(2)
Опубликована: Янв. 10, 2023
Abstract
Use
of
conversational
agents,
like
chatbots,
avatars,
and
robots
is
increasing
worldwide.
Yet,
their
effectiveness
in
health
care
largely
unknown.
The
aim
this
advanced
review
was
to
assess
the
use
agents
various
fields
care.
A
literature
search,
analysis,
synthesis
were
conducted
February
2022
PubMed
CINAHL.
included
evidence
analyzed
narratively
by
employing
principles
thematic
analysis.
We
reviewed
articles
on
artificial
intelligence‐based
question‐answering
systems
Most
identified
report
its
effectiveness;
less
known
about
use.
outlined
study
findings
explored
directions
future
research,
provide
evidence‐based
knowledge
systems.
This
article
categorized
under:
Fundamental
Concepts
Data
Knowledge
>
Human
Centricity
User
Interaction
Application
Areas
Health
Care
Technologies
Artificial
Intelligence
IEEE Transactions on Engineering Management,
Год журнала:
2023,
Номер
71, С. 10232 - 10244
Опубликована: Авг. 2, 2023
Studies
on
Chatbot
adoption
are
gaining
traction
across
different
fields.
Previous
studies
have
outlined
several
drivers
of
through
the
lenses
various
technology
theories.
However,
these
not
been
thoroughly
reviewed
and
synthesized.
Therefore,
this
article
aims
to
analyze
theories,
antecedents,
moderators,
domains,
methodologies,
participants
a
multiperspective
viewpoint.
Out
3942
collected,
219
were
analyzed.
The
main
findings
indicated
that
acceptance
model,
social
presence
theory,
computers
actors
dominant
theories
in
explaining
adoption.
Most
focused
examining
usage
intention
Chatbots,
with
limited
investigations
actual
use
continuous
intention.
Nearly
63%
analyzed
did
employ
those
tend
do
so
most
frequently
gender,
Chatbot/technical
experience,
age.
This
presents
fresh
viewpoint
deepens
our
understanding
proposes
agendas
for
future
research.
agenda
incorporates
research
directions
Chatbots
general
generative
artificial
intelligence
specific.
It
also
offers
theoretical
contributions
provides
relevant
information
developers,
decision-makers,
practitioners,
IT
vendors,
policymakers.
Electronics,
Год журнала:
2024,
Номер
13(7), С. 1331 - 1331
Опубликована: Апрель 2, 2024
The
Metaverse
and
Natural
Language
Processing
(NLP)
technologies
have
combined
to
fundamentally
change
the
nature
of
digital
sociability.
Our
understanding
social
interaction
needs
be
reevaluated
as
Metaverse’s
influence
spreads
into
more
areas
daily
life,
such
AI-driven
gaming,
interactive
training
companions,
museum
exhibits,
personalized
fitness
coaching,
virtual
mental
health
assistance,
language
translation
services,
tour
guiding,
conferencing.
This
study
analyzes
how
NLP
is
changing
relationships
in
these
applications.
We
examine
algorithms
societal
norms,
individual
behaviors,
interpersonal
connections,
improve
user
experience
using
a
multi-method
approach
incorporating
surveys
sentiment
analysis.
study’s
findings
show
can
enhance
experiences
while
also
pointing
out
related
issues
like
potential
bias
moral
problems.
provides
foundational
analysis,
shedding
light
on
challenges
negotiating
environment
that
molded
by
cutting-edge
NLP.
It
offers
stakeholders
academia
public
policy
essential
assistance
helps
them
understand
manage
complex
ramifications
this
socio-technological
paradigm.
Journal of Medical Internet Research,
Год журнала:
2024,
Номер
26, С. e46036 - e46036
Опубликована: Март 12, 2024
Background
A
plethora
of
weight
management
apps
are
available,
but
many
individuals,
especially
those
living
with
overweight
and
obesity,
still
struggle
to
achieve
adequate
loss.
An
emerging
area
in
is
the
support
for
one’s
self-regulation
over
momentary
eating
impulses.
Objective
This
study
aims
examine
feasibility
effectiveness
a
novel
artificial
intelligence–assisted
app
improving
behaviors
Southeast
Asian
cohort.
Methods
single-group
pretest-posttest
was
conducted.
Participants
completed
1-week
run-in
period
12-week
app-based
program
called
Eating
Trigger-Response
Inhibition
Program
(eTRIP).
self-monitoring
system
built
upon
3
main
components,
namely,
(1)
chatbot-based
check-ins
on
lapse
triggers,
(2)
food-based
computer
vision
image
recognition
(system
based
local
food
items),
(3)
automated
time-based
nudges
meal
stopwatch.
At
every
mealtime,
participants
were
prompted
take
picture
their
items,
which
identified
by
technology,
thereby
triggering
set
chatbot-initiated
questions
triggers
such
as
who
users
with.
Paired
2-sided
t
tests
used
compare
differences
psychobehavioral
constructs
before
after
7-day
program,
including
overeating
habits,
snacking
consideration
future
consequences,
behaviors,
anxiety,
depression,
physical
activity.
Qualitative
feedback
analyzed
content
analysis
according
4
steps,
decontextualization,
recontextualization,
categorization,
compilation.
Results
The
mean
age,
self-reported
BMI,
waist
circumference
31.25
(SD
9.98)
years,
28.86
7.02)
kg/m2,
92.60
18.24)
cm,
respectively.
There
significant
improvements
all
7
constructs,
except
anxiety.
After
adjusting
multiple
comparisons,
statistically
found
habits
(mean
–0.32,
SD
1.16;
P<.001),
–0.22,
1.12;
P<.002),
behavior
0.08,
0.49;
P=.007),
depression
–0.12,
0.74;
activity
1288.60,
3055.20
metabolic
equivalent
task-min/day;
P<.001).
Forty-one
reported
skipping
at
least
1
(ie,
breakfast,
lunch,
or
dinner),
summing
578
(67.1%)
862
meals
skipped.
Of
230
participants,
80
(34.8%)
provided
textual
that
indicated
satisfactory
user
experience
eTRIP.
Four
themes
emerged,
becoming
more
mindful
self-monitoring,
personalized
reminders
prompts
chatbot,
logging
recognition,
(4)
engaging
simple,
easy,
appealing
interface.
attrition
rate
8.4%
(21/251).
Conclusions
eTRIP
feasible
effective
be
tested
larger
population
its
sustainability
people
obesity.
Trial
Registration
ClinicalTrials.gov
NCT04833803;
https://classic.clinicaltrials.gov/ct2/show/NCT04833803
