Leveraging social media data to study disease and treatment characteristics of Hodgkin’s lymphoma Using Natural Language Processing methods
PLOS Digital Health,
Год журнала:
2025,
Номер
4(3), С. e0000765 - e0000765
Опубликована: Март 19, 2025
Background
The
use
of
social
media
platforms
in
health
research
is
increasing,
yet
their
application
studying
rare
diseases
limited.
Hodgkin’s
lymphoma
(HL)
a
malignancy
with
high
incidence
young
adults.
This
study
evaluates
the
feasibility
using
data
to
disease
and
treatment
characteristics
HL.
Methods
We
utilized
X
(formerly
Twitter)
API
v2
developer
portal
download
posts
tweets)
from
January
2010
October
2022.
Annotation
guidelines
were
developed
literature
manual
review
limited
was
performed
identify
class
attributes
(characteristics)
HL
discussed
on
X,
create
gold
standard
dataset.
dataset
subsequently
employed
train,
test,
validate
Named
Entity
Recognition
(NER)
Natural
Language
Processing
(NLP)
application.
Results
After
preparation,
80,811
collected:
500
for
annotation
guideline
development,
2,000
NLP
remaining
78,311
deploying
identified
nine
classes
related
HL,
such
as
classification,
etiopathology,
stages
progression,
treatment.
progression
most
frequently
discussed,
20,013
(25.56%)
mentioning
HL’s
treatments
17,177
(21.93%)
progression.
model
exhibited
robust
performance,
achieving
86%
accuracy
an
87%
F1
score.
etiopathology
demonstrated
excellent
93%
95%
Discussion
displayed
efficacy
extracting
characterizing
HL-related
information
posts,
evidenced
by
Nonetheless,
presented
limitations
distinguishing
between
patients,
providers,
caregivers
establishing
temporal
relationships
attributes.
Further
necessary
bridge
these
gaps.
Conclusion
Our
potential
valuable
preliminary
source
understanding
Lymphoma.
Язык: Английский
Applications of Natural Language Processing in Otolaryngology: A Scoping Review
The Laryngoscope,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 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.
Язык: Английский