Natural language processing in dermatology: A systematic literature review and state of the art
Journal of the European Academy of Dermatology and Venereology,
Journal Year:
2024,
Volume and Issue:
38(12), P. 2225 - 2234
Published: Aug. 16, 2024
Abstract
Background
Natural
Language
Processing
(NLP)
is
a
field
of
both
computational
linguistics
and
artificial
intelligence
(AI)
dedicated
to
analysis
interpretation
human
language.
Objectives
This
systematic
review
aims
at
exploring
all
the
possible
applications
NLP
techniques
in
dermatological
setting.
Methods
Extensive
search
on
‘natural
language
processing’
‘dermatology’
was
performed
MEDLINE
Scopus
electronic
databases.
Only
journal
articles
with
full
text
electronically
available
English
translation
were
considered.
The
PICO
(Population,
Intervention
or
exposure,
Comparison,
Outcome)
algorithm
applied
our
study
protocol.
Results
have
been
utilized
across
various
domains,
including
atopic
dermatitis,
acne/rosacea,
skin
infections,
non‐melanoma
cancers
(NMSCs),
melanoma
skincare.
There
versatility
data
extraction
from
diverse
sources
such
as
health
records
(EHRs),
social
media
platforms
online
forums.
We
found
extensive
utilization
showcasing
its
potential
extracting
valuable
insights
informing
diagnosis,
treatment
optimization,
patient
preferences
unmet
needs
research
clinical
practice.
Conclusions
While
shows
promise
enhancing
practice,
challenges
quality,
ambiguity,
lack
standardization
privacy
concerns
necessitate
careful
consideration.
Collaborative
efforts
between
dermatologists,
scientists
ethicists
are
essential
for
addressing
these
maximizing
dermatology.
Language: Английский
Assessing the Impact of ChatGPT in Dermatology: A Comprehensive Rapid Review
Journal of Clinical Medicine,
Journal Year:
2024,
Volume and Issue:
13(19), P. 5909 - 5909
Published: Oct. 3, 2024
Background/Objectives:
The
use
of
artificial
intelligence
(AI)
in
dermatology
is
expanding
rapidly,
with
ChatGPT,
a
large
language
model
(LLM)
from
OpenAI,
showing
promise
patient
education,
clinical
decision-making,
and
teledermatology.
Despite
its
potential,
the
ethical,
clinical,
practical
implications
application
remain
insufficiently
explored.
This
study
aims
to
evaluate
effectiveness,
challenges,
future
prospects
ChatGPT
dermatology,
focusing
on
applications,
interactions,
medical
writing.
was
selected
due
broad
adoption,
extensive
validation,
strong
performance
dermatology-related
tasks.
Methods:
A
thorough
literature
review
conducted,
publications
related
dermatology.
search
included
articles
English
November
2022
August
2024,
as
this
period
captures
most
recent
developments
following
launch
2022,
ensuring
that
includes
latest
advancements
discussions
role
Studies
were
chosen
based
their
relevance
ethical
issues.
Descriptive
metrics,
such
average
accuracy
scores
reliability
percentages,
used
summarize
characteristics,
key
findings
analyzed.
Results:
has
shown
significant
potential
passing
specialty
exams
providing
reliable
responses
queries,
especially
for
common
dermatological
conditions.
However,
it
faces
limitations
diagnosing
complex
cases
like
cutaneous
neoplasms,
concerns
about
completeness
information
persist.
Ethical
issues,
including
data
privacy,
algorithmic
bias,
need
transparent
guidelines,
identified
critical
challenges.
Conclusions:
While
significantly
enhance
practice,
particularly
education
teledermatology,
integration
must
be
cautious,
addressing
complementing,
rather
than
replacing,
dermatologist
expertise.
Future
research
should
refine
ChatGPT’s
diagnostic
capabilities,
mitigate
biases,
develop
comprehensive
guidelines.
Language: Английский
Usefulness of the large language model ChatGPT (GPT‐4) as a diagnostic tool and information source in dermatology
JEADV Clinical Practice,
Journal Year:
2024,
Volume and Issue:
unknown
Published: June 3, 2024
Abstract
Background
The
field
of
artificial
intelligence
is
rapidly
evolving.
As
an
easily
accessible
platform
with
vast
user
engagement,
the
Chat
Generative
Pre‐Trained
Transformer
(ChatGPT)
holds
great
promise
in
medicine,
latest
version,
GPT‐4,
capable
analyzing
clinical
images.
Objectives
To
evaluate
ChatGPT
as
a
diagnostic
tool
and
information
source
dermatology.
Methods
A
total
15
images
were
selected
from
Danish
web
atlas,
Danderm,
depicting
various
common
rare
skin
conditions.
uploaded
to
version
which
was
prompted
‘Please
provide
description,
potential
diagnosis,
treatment
options
for
following
dermatological
condition’.
generated
responses
assessed
by
senior
registrars
dermatology
consultant
dermatologists
terms
accuracy,
relevance,
depth
(scale
1–5),
addition,
image
quality
rated
0–10).
Demographic
professional
about
respondents
registered.
Results
23
physicians
participated
study.
majority
(83%),
48%
had
more
than
10
years
training.
overall
median
rating
out
[interquartile
range
(IQR):
9–10].
2
(IQR:
1–4),
while
ratings
3
2–4)
1–3),
respectively.
Conclusions
Despite
advancements
ChatGPT,
including
newly
added
processing
capabilities,
chatbot
demonstrated
significant
limitations
providing
reliable
clinically
useful
illustrative
Language: Английский
ChatGPT for skin cancer prevention: High patients' satisfaction to educational material
JEADV Clinical Practice,
Journal Year:
2024,
Volume and Issue:
3(4), P. 1283 - 1287
Published: March 1, 2024
In
this
rapidly
evolving
technological
era,
ChatGPT
represents
a
significant
breakthrough
in
the
field
of
artificial
intelligence
(AI),
being
pivotal
source
virtual
content
generation.1
Developed
by
OpenAI,
harnesses
potential
natural
language
processing
(NLP)
to
craft
coherent
and
pertinent
responses
language.
As
knowledgeable
assistant,
it
can
provide
insights
into
multitude
health-related
topics,
including
medical
education,
with
patients
relevant
information.2
skin
cancers,
advanced
AI
healthcare
system
may
act
synergically
enhance
knowledge
general
population.
We
conducted
survey
assess
patients'
satisfaction
ChatGPT's
common
questions
about
cancers.
adopted
US
Skin
Cancer
Foundation's
pre-existing
10-question
interactive
quiz,
an
educational
tool
for
informing
cancer
prevention.3
The
were
administered
freely
available
ChatGPT-3.5
verified
consensus
panel
10
dermatologists,
affirming
accuracy
9
answers.
Hence,
questionnaire
(translated
Italian
using
same
version
ChatGPT),
was
220
subjects
consecutively
accessing
dermatology
outpatient
service
screening
visits
from
1
July
2023
September
2023;
participants
asked
rate
their
each
response
according
Likert
scale
(1—very
dissatisfied
5—very
satisfied).
Additionally,
evaluated
clarity,
comprehensiveness
material,
improvement
cancer.
correctly
completed
199/220
(90.5%)
patients,
that
represented
sample
investigated.
Subjects
included
99
(49.7%)
males
100
females
(50.3%),
mean
age
50
years
(SD
=
16.1).
A
percentage
had
high
degree
(44.7%
upper
secondary
school,
35.2%
university.
majority
(40.2%)
employees,
while
23.6%
self-employed
and/or
contractors.
Most
provided
regarded
as
shown
Table
1.
When
assessing
clarity
comprehensibility,
defined
themselves
"very
satisfied"
(47.7%)
language,
"satisfied"
(44.7%)
level
information
exhaustiveness
answers,
(43.7%)
increase
they
gained
questionnaire.
Almost
half
resulted
44.7%
"satisfied";
preferred
knowledge.
No
associations
found
between
clinical
data
expressed.
Limit
sun
exposure:
Avoid
direct
exposure
during
peak
hours
(from
10:00
AM
4:00
PM)
when
sun's
rays
are
most
intense.
Seek
shade
wear
protective
clothing,
wide-brimmed
hats,
sunglasses.
Use
sunscreen:
Apply
broad-spectrum
sunscreen
SPF
before
going
outdoors.
Reapply
every
2
h,
especially
after
swimming
or
sweating.
tanning
beds:
Tanning
beds
emit
harmful
UV
risk
Completely
avoid
use
beds.
Perform
self-exams:
Regularly
examine
your
any
moles,
freckles,
other
lesions
change
appearance
size.
If
you
notice
changes,
consult
dermatologist.
Stay
hydrated:
Drinking
plenty
water
helps
maintain
healthy
resilient
skin.
Healthy
lifestyle:
Maintain
balanced
diet
rich
antioxidants
vitamins,
smoking,
reduce
excessive
alcohol
consumption.
Protect
children:
Keep
infants
under
6
months
away
sunlight
clothing
on
older
children.
Regular
checkups:
Schedule
regular
dermatologist
screening,
if
have
family
history
disease
factors.
Remember
prevention
early
diagnosis
crucial
reducing
Overall
presents
real
opportunity
accessibility
information,4-8
our
suggest
great
value
supporting
patient
together
score
satisfaction.
This
is
first
report
describing
assessment
awareness.
However,
risks
encountering
inaccurate
give
rise
ethical
concerns.
Our
research
identified
1/10
question
generated
incorrect
(n.8
1),
finding
line
Johnson
et
al.,
which
reported
8.3%
inaccuracy
rate.9
be
integrated
healthcare,
should
accompanied
oversight
ensure
provided.
Conceptualization:
E.
De
Luca
A.
Chiricozzi.
Methodology:
G.
Coscarella.
Original
draft
preparation:
S.
Cappilli.
Review
editing:
Chiricozzi
K.
Peris.
Supervision:
All
authors
read
agreed
published
manuscript.
Peris
has
received
consulting
fees
honoraria
unrelated
work
Abbvie,
Almirall,
Biogen,
Celgene,
Janssen
Galderma,
Novartis,
Lilly,
Pierre
Fabre,
Sandoz,
Sanofi
Sun
Pharma,
outside
submitted
work;
AbbVie,
Boehringer-Ingelheim,
Bristol
Myers
Squibb,
Leo
Janssen,
Pfizer,
Genzyme,
all
declare
no
conflicts
interest
study
accordance
Declaration
Helsinki.
manuscript
given
written
informed
consent
participation
deidentified,
anonymized,
aggregated
case
details
publication.
Language: Английский
Skin and Digital–The 2024 Narrative
Mayo Clinic Proceedings Digital Health,
Journal Year:
2024,
Volume and Issue:
2(3), P. 322 - 330
Published: May 27, 2024
The
global
burden
of
skin
diseases
affects
over
three
billion
individuals,
posing
significant
public
health
challenges
worldwide,
with
profound
impacts
in
both
high-income
and
low-
middle-income
countries
(LMICs).
These
are
exacerbated
by
widespread
disparities
access
to
dermatological
care
the
prevalence
misinformation.
This
paper,
derived
from
Skin
&
Digital
Summit
at
"International
Master
Course
on
Aging
Science
(IMCAS)
critically
evaluates
how
digital
technologies
such
as
artificial
intelligence
(AI),
tele-dermatology,
large
language
models
(LLMs)
can
bridge
these
gaps.
It
explores
practical
applications
case
studies
demonstrating
impact
various
settings,
a
particular
focus
adapting
solutions
meet
diverse
needs
LMICs.
Additionally,
narrative
highlights
ongoing
conversation
within
community
about
role
advances
healthcare,
emphasizing
that
this
discussion
is
dynamic
one
continuously
evolving.
Dermatologists
play
an
essential
transition,
integrating
tools
into
mainstream
complement
patient-centred,
culturally
sensitive
approach.
paper
advocates
for
globally
coordinated
response
not
only
addresses
current
but
also
promotes
equitable
resources,
making
more
representative
all
types
accessible
worldwide.
Language: Английский
Evaluating the efficacy of ChatGPT in addressing patient queries about acne and atopic dermatitis
Clinical and Experimental Dermatology,
Journal Year:
2024,
Volume and Issue:
49(10), P. 1253 - 1255
Published: May 9, 2024
In
this
study,
we
evaluated
ChatGPT
3.5
responses
to
common
patient
questions
about
acne
and
atopic
dermatitis.
While
generally
provided
accurate
comprehensive
answers,
its
readability
was
at
the
college
level,
which
is
above
recommended
grade
for
materials.
Significant
information
gaps
were
also
noted,
including
omissions
of
newer
treatments,
probably
because
model’s
training
limitations
up
mid-2021.
Despite
these
limitations,
can
be
a
valuable
resource,
especially
in
regions
where
dermatological
expertise
scarce.
Language: Английский
Enhancing performance factor analysis through skill profile and item similarity integration via an attention mechanism of artificial intelligence
Frontiers in Education,
Journal Year:
2024,
Volume and Issue:
9
Published: Nov. 15, 2024
Introduction
Frequent
formative
assessment
is
essential
for
accurately
evaluating
student
learning,
enhancing
engagement,
and
providing
personalized
feedback.
In
STEM
education,
understanding
the
relationship
between
skills
that
students
have
internalized
(mastered)
those
they
are
developing
(emergent)
crucial.
Traditional
models,
including
item
response
cognitive
diagnosis
primarily
focus
on
emergent
skills,
often
overlooking
skills.
Moreover,
new
tools
like
large
language
models
lack
a
complete
approach
tracking
knowledge
capturing
complex
skill
relationships.
Methods
This
study
incorporates
artificial
intelligence,
specifically
attention
mechanisms,
into
educational
to
evaluate
both
We
propose
modified
version
of
Performance
Factor
Analysis
(PFA),
which
assesses
abilities
by
analyzing
past
responses
comparing
them
with
peer
performance
same
items,
using
parameters
from
sigmoid
function.
model
leverages
mechanisms
capture
order-based
similarity
decay
principles,
nuanced
view
profiles.
Results
The
Modified
significantly
improved
discriminative
power,
accuracy,
precision,
recall,
F1
scores
across
various
areas
compared
traditional
PFA
models.
Discussion
These
results
indicate
allows
more
accurate
comprehensive
evaluation
performance,
effectively
identifying
By
integrating
AI
assessment,
educators
gain
deeper
insights,
enabling
refine
teaching
strategies
better
support
students'
mastery
types
Language: Английский