Large language models in patient education: a scoping review of applications in medicine
Serhat Aydın,
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Mert Karabacak,
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Victoria Vlachos
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et al.
Frontiers in Medicine,
Journal Year:
2024,
Volume and Issue:
11
Published: Oct. 29, 2024
Large
Language
Models
(LLMs)
are
sophisticated
algorithms
that
analyze
and
generate
vast
amounts
of
textual
data,
mimicking
human
communication.
Notable
LLMs
include
GPT-4o
by
Open
AI,
Claude
3.5
Sonnet
Anthropic,
Gemini
Google.
This
scoping
review
aims
to
synthesize
the
current
applications
potential
uses
in
patient
education
engagement.
Language: Английский
Artificial Intelligence for Language Translation
JAMA,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Sept. 12, 2024
This
Viewpoint
discusses
the
challenges
to
implementing
artificial
intelligence–based
translation
in
clinical
settings
and
what
health
care
organizations
can
do
mitigate
these
challenges.
Language: Английский
Applications of Natural Language Processing in Otolaryngology: A Scoping Review
The Laryngoscope,
Journal Year:
2025,
Volume and Issue:
unknown
Published: May 1, 2025
To
review
the
current
literature
on
applications
of
natural
language
processing
(NLP)
within
field
otolaryngology.
MEDLINE,
EMBASE,
SCOPUS,
Cochrane
Library,
Web
Science,
and
CINAHL.
The
preferred
reporting
Items
for
systematic
reviews
meta-analyzes
extension
scoping
checklist
was
followed.
Databases
were
searched
from
date
inception
up
to
Dec
26,
2023.
Original
articles
application
language-based
models
otolaryngology
patient
care
research,
regardless
publication
date,
included.
studies
classified
under
2011
Oxford
CEBM
levels
evidence.
One-hundred
sixty-six
papers
with
a
median
year
2024
(range
1982,
2024)
Sixty-one
percent
(102/166)
used
ChatGPT
published
in
2023
or
2024.
Sixty
NLP
clinical
education
decision
support,
42
education,
14
electronic
medical
record
improvement,
5
triaging,
4
trainee
monitoring,
3
telemedicine,
1
translation.
For
37
extraction,
classification,
analysis
data,
17
thematic
analysis,
evaluating
scientific
reporting,
manuscript
preparation.
role
is
evolving,
passing
OHNS
board
simulations,
though
its
requires
improvement.
shows
potential
post-treatment
monitoring.
effective
at
extracting
data
unstructured
large
sets.
There
limited
research
administrative
tasks.
Guidelines
use
are
critical.
Language: Английский
Automated Assessment of Reporting Completeness in Orthodontic Research Using LLMs: An Observational Study
Applied Sciences,
Journal Year:
2024,
Volume and Issue:
14(22), P. 10323 - 10323
Published: Nov. 10, 2024
This
study
evaluated
the
usability
of
Large
Language
Models
(LLMs),
specifically
ChatGPT,
in
assessing
completeness
reporting
orthodontic
research
abstracts.
We
focused
on
two
key
areas:
randomized
controlled
trials
(RCTs)
and
systematic
reviews,
using
CONSORT-A
PRISMA
guidelines
for
evaluation.
Twenty
RCTs
twenty
reviews
published
between
2018
2022
leading
journals
were
analyzed.
The
results
indicated
that
ChatGPT
achieved
perfect
agreement
with
human
reviewers
several
fundamental
items;
however,
significant
discrepancies
noted
more
complex
areas,
such
as
randomization
eligibility
criteria.
These
findings
suggest
while
LLMs
can
enhance
efficiency
literature
appraisal,
they
should
be
used
conjunction
expertise
to
ensure
a
comprehensive
underscores
need
further
refinement
improve
their
performance
quality
orthodontics
other
fields.
Language: Английский