Dental Traumatology,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 24, 2025
ABSTRACT
Background
This
study
assessed
the
accuracy
and
consistency
of
responses
provided
by
six
Artificial
Intelligence
(AI)
applications,
ChatGPT
version
3.5
(OpenAI),
4
4.0
Perplexity
(Perplexity.AI),
Gemini
(Google),
Copilot
(Bing),
to
questions
related
emergency
management
avulsed
teeth.
Materials
Methods
Two
pediatric
dentists
developed
18
true
or
false
regarding
dental
avulsion
asked
public
chatbots
for
3
days.
The
were
recorded
compared
with
correct
answers.
SPSS
program
was
used
calculate
obtained
accuracies
their
consistency.
Results
achieved
highest
rate
95.6%
over
entire
time
frame,
while
(Perplexity.AI)
had
lowest
67.2%.
(OpenAI)
only
AI
that
perfect
agreement
real
answers,
except
at
noon
on
day
1.
showed
weakest
(6
times).
Conclusions
With
exception
ChatGPT's
paid
version,
4.0,
do
not
seem
ready
use
as
main
resource
in
managing
teeth
during
emergencies.
It
might
prove
beneficial
incorporate
International
Association
Dental
Traumatology
(IADT)
guidelines
chatbot
databases,
enhancing
Journal of Clinical Pathology,
Год журнала:
2024,
Номер
unknown, С. jcp - 209304
Опубликована: Янв. 10, 2024
Aims
To
evaluate
the
accuracy
of
Chat
Generative
Pre-trained
Transformer
(ChatGPT)
powered
by
GPT-4
in
histopathological
image
detection
and
classification
colorectal
adenomas
using
diagnostic
consensus
provided
pathologists
as
a
reference
standard.
Methods
A
study
was
conducted
with
100
polyp
photomicrographs,
comprising
an
equal
number
non-adenomas,
classified
two
pathologists.
These
images
were
analysed
classic
for
1
time
October
2023
custom
20
times
December
2023.
GPT-4’s
responses
compared
against
standard
through
statistical
measures
to
its
proficiency
diagnosis,
further
assessing
model’s
descriptive
accuracy.
Results
demonstrated
median
sensitivity
74%
specificity
36%
adenoma
detection.
The
varied,
ranging
from
16%
non-specific
changes
tubular
adenomas.
Its
consistency,
indicated
low
kappa
values
0.06
0.11,
suggested
only
poor
slight
agreement.
All
microscopic
descriptions
corresponded
their
diagnoses.
also
commented
about
limitations
diagnoses
(eg,
slide
diagnosis
best
done
pathologists,
inadequacy
single-image
conclusions,
need
clinical
data
higher
magnification
view).
Conclusions
showed
high
but
detecting
varied
classification.
However,
consistency
low.
This
artificial
intelligence
tool
acknowledged
limitations,
emphasising
pathologist’s
expertise
additional
context.
Humanities and Social Sciences Communications,
Год журнала:
2024,
Номер
11(1)
Опубликована: Март 15, 2024
Abstract
The
purpose
of
this
research
is
to
identify
and
evaluate
the
technical,
ethical
regulatory
challenges
related
use
Artificial
Intelligence
(AI)
in
healthcare.
potential
applications
AI
healthcare
seem
limitless
vary
their
nature
scope,
ranging
from
privacy,
research,
informed
consent,
patient
autonomy,
accountability,
health
equity,
fairness,
AI-based
diagnostic
algorithms
care
management
through
automation
for
specific
manual
activities
reduce
paperwork
human
error.
main
faced
by
states
regulating
were
identified,
especially
legal
voids
complexities
adequate
regulation
better
transparency.
A
few
recommendations
made
protect
data,
mitigate
risks
regulate
more
efficiently
international
cooperation
adoption
harmonized
standards
under
World
Health
Organization
(WHO)
line
with
its
constitutional
mandate
digital
public
health.
European
Union
(EU)
law
can
serve
as
a
model
guidance
WHO
reform
International
Regulations
(IHR).
Dental Traumatology,
Год журнала:
2024,
Номер
40(6), С. 722 - 729
Опубликована: Май 14, 2024
This
study
assessed
the
consistency
and
accuracy
of
responses
provided
by
two
artificial
intelligence
(AI)
applications,
ChatGPT
Google
Bard
(Gemini),
to
questions
related
dental
trauma.
Health care science,
Год журнала:
2024,
Номер
3(5), С. 329 - 349
Опубликована: Окт. 1, 2024
Abstract
The
increasing
integration
of
new
technologies
is
driving
a
fundamental
revolution
in
the
healthcare
sector.
Developments
artificial
intelligence
(AI),
machine
learning,
and
big
data
analytics
have
completely
transformed
diagnosis,
treatment,
care
patients.
AI‐powered
solutions
are
enhancing
efficiency
accuracy
delivery
by
demonstrating
exceptional
skills
personalized
medicine,
early
disease
detection,
predictive
analytics.
Furthermore,
telemedicine
remote
patient
monitoring
systems
overcome
geographical
constraints,
offering
easy
accessible
services,
particularly
underserved
areas.
Wearable
technology,
Internet
Medical
Things,
sensor
empowered
individuals
to
take
an
active
role
tracking
managing
their
health.
These
devices
facilitate
real‐time
collection,
enabling
preventive
care.
Additionally,
development
3D
printing
technology
has
revolutionized
medical
field
production
customized
prosthetics,
implants,
anatomical
models,
significantly
impacting
surgical
planning
treatment
strategies.
Accepting
these
advancements
holds
potential
create
more
patient‐centered,
efficient
system
that
emphasizes
individualized
care,
better
overall
health
outcomes.
This
review's
novelty
lies
exploring
how
radically
transforming
industry,
paving
way
for
effective
all.
It
highlights
capacity
modern
revolutionize
addressing
long‐standing
challenges
improving
Although
approval
use
digital
advanced
analysis
face
scientific
regulatory
obstacles,
they
translational
research.
as
continue
evolve,
poised
alter
environment,
sustainable,
efficient,
ecosystem
future
generations.
Innovation
across
multiple
fronts
will
shape
revolutionizing
provision
healthcare,
outcomes,
equipping
both
patients
professionals
with
tools
make
decisions
receive
treatment.
As
develop
become
integrated
into
standard
practices,
probably
be
accessible,
effective,
than
ever
before.
New Asian Journal of Medicine,
Год журнала:
2024,
Номер
2(1), С. 1 - 16
Опубликована: Янв. 1, 2024
Background:
In
the
rapidly
evolving
domain
of
healthcare
technology,
integration
advanced
computational
models
has
opened
up
new
possibilities
for
personalized
nutrition
guidance.
The
emergence
sophisticated
language
models,
such
as
Chat
Generative
Pre-training
Transformer
(ChatGPT),
offers
potential
in
providing
interactive
and
tailored
dietary
advice.
However,
concerns
remain
about
applicability
appropriateness
ChatGPT's
recommendations,
especially
those
with
distinct
health
conditions.
Objectives:
This
study
aimed
to
evaluate
reliability
ChatGPT
a
source
nutritional
Methods:
Three
hypothetical
scenarios
representing
various
conditions
were
presented
alongside
precise
requirements.
was
tasked
generate
programs,
encompassing
meal
timing,
specific
caloric
portions
(measured
grams
spoons),
well
alternative
options
each
scenario.
Following
this,
ChatGPT’s
generated
programs
underwent
thorough
review
by
multidisciplinary
team
nutritionist,
specialist
physicians
clinical
researchers.
evaluation
focused
on
programs'
suitability,
alignment
standards,
consideration
individual
factors,
additional
guidance
Safety.
Results:
demonstrated
its
ability
plans
accordance
basic
principles.
there
are
apparent
issues
recommended
macronutrient
distribution,
handling
conditions,
drug
interactions,
setting
realistic
weight
loss
goals.
Conclusions:
While
exhibits
promise
program
generator,
application
intervention
should
be
restricted
certified
professionals.
Until
July
2023,
it
is
not
advisable
patients
engage
self-prescription
using
version
3.5,
owing
inability
provide
professional
knowledge
acceptable
guidance,
particularly
individuals
co-existing
prevailing
absence
reasoning
highlights
importance
employing
solely
tool,
rather
than
relying
an
autonomous
decision-maker.
Its
lack
highlighted
need
human
expert
collaboration
evaluations.
PubMed,
Год журнала:
2024,
Номер
19(2), С. 85 - 98
Опубликована: Янв. 1, 2024
Artificial
intelligence
(AI)
is
transforming
the
diagnostic
methods
and
treatment
approaches
in
constantly
evolving
field
of
endodontics.
The
current
review
discusses
recent
advancements
AI;
with
a
specific
focus
on
convolutional
artificial
neural
networks.
Apparently,
AI
models
have
proved
to
be
highly
beneficial
analysis
root
canal
anatomy,
detecting
periapical
lesions
early
stages
as
well
providing
accurate
working-length
determination.
Moreover,
they
seem
effective
predicting
success
next
identifying
various
conditions
e.g.,
dental
caries,
pulpal
inflammation,
vertical
fractures,
expression
second
opinions
for
non-surgical
treatments.
Furthermore,
has
demonstrated
an
exceptional
ability
recognize
landmarks
cone-beam
computed
tomography
scans
consistently
high
precision
rates.
While
significantly
promoted
accuracy
efficiency
endodontic
procedures,
it
importance
continue
validating
reliability
practicality
possible
widespread
integration
into
daily
clinical
practice.
Additionally,
ethical
considerations
related
patient
privacy,
data
security,
potential
bias
should
carefully
examined
ensure
responsible
implementation
