PLoS ONE,
Год журнала:
2025,
Номер
20(1), С. e0315216 - e0315216
Опубликована: Янв. 14, 2025
In
this
paper,
we
explore
the
application
of
Artificial
Intelligence
and
network
science
methodologies
in
characterizing
interdisciplinary
disciplines,
with
a
specific
focus
on
field
Italian
design,
taken
as
paradigmatic
example.
Exploratory
data
analysis
study
academic
collaboration
networks
highlight
how
is
evolving
towards
increased
collaboration.
Text
semantic
topic
modelling
identified
evolution
research
interest
over
time,
defining
ranking
pairs
keywords
three
prominent
topics:
User-Centric
Experience
Design,
Innovative
Product
Design
Sustainable
Service
Design.
Our
results
revealed
significant
transformation
field,
shift
from
individual
to
collaborative
research,
evidenced
by
increasing
complexity
within
groups.
We
acknowledge
limitations
faced
work,
suggesting
that
methodology
may
be
primarily
suitable
for
bibliometric
more
silos-like
disciplines.
However,
emphasize
urgency
scientific
community
address
future
not
indexed
large
open-access
databases
like
OpenAlex.
Frontiers in Immunology,
Год журнала:
2025,
Номер
16
Опубликована: Март 7, 2025
The
development
of
effective
vaccines
is
crucial
for
combating
current
and
emerging
pathogens.
Despite
significant
advances
in
the
field
vaccine
there
remain
numerous
challenges
including
lack
standardized
data
reporting
curation
practices,
making
it
difficult
to
determine
correlates
protection
from
experimental
clinical
studies.
Significant
gaps
knowledge
integration
can
hinder
which
relies
on
a
comprehensive
understanding
interplay
between
pathogens
host
immune
system.
In
this
review,
we
explore
landscape
development,
highlighting
computational
challenges,
limitations,
opportunities
associated
with
integrating
diverse
types
leveraging
artificial
intelligence
(AI)
machine
learning
(ML)
techniques
design.
We
discuss
role
natural
language
processing,
semantic
integration,
causal
inference
extracting
valuable
insights
published
literature
unstructured
sources,
as
well
modeling
responses.
Furthermore,
highlight
specific
uncertainty
quantification
emphasize
importance
establishing
formats
ontologies
facilitate
analysis
heterogeneous
data.
Through
harmonization
safe
be
accelerated
improve
public
health
outcomes.
Looking
future,
need
collaborative
efforts
among
researchers,
scientists,
experts
realize
full
potential
AI-assisted
design
streamline
process.
Neurotrauma Reports,
Год журнала:
2024,
Номер
5(1), С. 203 - 214
Опубликована: Март 1, 2024
Traumatic
brain
injury
(TBI)
has
evolved
from
a
topic
of
relative
obscurity
to
one
widespread
scientific
and
lay
interest.The
scope
focus
TBI
research
have
shifted,
trends
changed
in
response
public
interest.This
study
two
primary
goals:
first,
identify
the
predominant
themes
research;
second,
delineate
''hot''
''cold''
areas
interest
by
evaluating
current
popularity
or
decline
these
topics.Hot
topics
may
be
dwarfed
absolute
numbers
other,
larger
but
are
rapidly
gaining
interest.Likewise,
cold
present
opportunities
for
researchers
revisit
unanswered
questions.We
utilized
BER-Topic,
an
advanced
natural
language
processing
(NLP)-based
technique,
analyze
articles
published
since
1990.This
approach
facilitated
identification
key
extracting
sets
distinctive
keywords
representative
each
article's
core
themes.Using
topics'
probabilities,
we
trained
linear
regression
models
detect
over
time,
recognizing
that
were
(hot)
losing
(cold)
relevance.Additionally,
conducted
specific
analysis
focusing
on
observed
decade
(the
2020s).Our
modeling
categorized
42,422
into
27
distinct
topics.The
10
most
frequently
occurring
were:
''Rehabilitation,''
''Molecular
Mechanisms
TBI,''
''Concussion,''
''Repetitive
Head
Impacts,''
''Surgical
Interventions,''
''Biomarkers,'
'
'Intracranial
Pressure,''
''Posttraumatic
Neurodegeneration,''
'Chronic
Encephalopathy,''
''Blast
Induced
while
our
trend
indicated
hottest
''Genomics,''
''Sex
Hormones,''
''Diffusion
Tensor
Imaging,''
cooling
Sleep,''
''Sensory
Functions,''
''Hyperosmolar
Therapies.''This
highlights
dynamic
nature
underscores
shifting
emphasis
within
field.The
findings
can
aid
emerging
where
there
is
little
new
reported.By
utilizing
NLP
effectively
synthesize
extensive
collection
TBI-related
scholarly
literature,
demonstrate
potential
machine
learning
techniques
understanding
guiding
future
prospects.This
stage
similar
analyses
other
medical
disciplines,
offering
profound
insights
further
exploration.
Healthcare,
Год журнала:
2024,
Номер
12(22), С. 2309 - 2309
Опубликована: Ноя. 19, 2024
During
the
COVID-19
pandemic,
paracetamol
was
widely
recommended
in
different
clinical
settings,
and
sometimes
advised
over
non-steroidal
anti-inflammatory
drugs
(NSAIDs).
These
recommendations
sparked
a
strong
debate,
with
reports
suggesting
either
potential
benefits
or
harms
for
individuals
infected
SARS-CoV-2.
As
no
systematic
review
is
available,
we
performed
meta-analysis
to
estimate
impact
of
on
outcomes
compared
placebo,
use,
NSAIDs.
Frontiers in Research Metrics and Analytics,
Год журнала:
2023,
Номер
8
Опубликована: Март 24, 2023
While
the
COVID-19
pandemic
morphs
into
less
malignant
forms,
virus
has
spawned
a
series
of
poorly
understood,
post-infection
symptoms
with
staggering
ramifications,
i.
e.,
long
COVID
(LC).
This
bibliometric
study
profiles
rapidly
growing
LC
research
domain
[5,243
articles
from
PubMed
and
Web
Science
(WoS)]
to
make
its
knowledge
content
more
accessible.
The
article
addresses
What?
Where?
Who?
When?
questions.
A
13-topic
Concept
Grid
presents
bottom-up
topic
clusters.
We
break
out
those
topics
other
data
fields,
including
disciplinary
concentrations,
topical
details,
information
on
"players"
(countries,
institutions,
authors)
engaging
in
topics.
provide
access
results
Objective
Since
unexpected
COVID-19
has
been
causing
massive
losses
worldwide,
preventive
measures
have
emergency
provided
to
curb
the
expansion
of
epidemic
and
cut
off
transmission
routes.
However,
there
is
a
lack
studies
that
comprehensively
address
infection
prevention
measures.
This
aims
provide
comprehensive
evaluation
framework
identify
factors
impacting
prevention.
Meanwhile,
categorizing
into
individual,
social,
environmental,
technological
dimensions
uncovering
their
interrelationships
level
importance
are
indeed
novelties
this
study.
Methods
An
integration
fuzzy
logic
decision-making
trial
laboratory
(DEMATEL)
utilized,
data
was
collected
from
panel
professional
experts
in
Malaysia.
Using
cause-effect
relationship
diagram,
DEMATEL
method
evaluates
causal
relationships
between
factors.
Results
Findings
showed
environmental
play
most
significant
roles
preventing
infection,
followed
by
technology,
social
Getting
vaccinated
crucial
factor
dimension
cutting
spread
COVID-19.
Telehealth,
use
personal
protective
equipments
(PPEs),
adoption
distancing
important
individual
dimensions,
respectively.
Conclusions
study
offered
valuable
insights
for
policymakers
healthcare
professionals
designing
implementing
effective
strategies
prevent
pandemic
disease
transmission.
can
be
practically
applied
optimize
prioritize
measures,
assign
resources
more
effectively,
guide
evidence-based
face
evolving
situations.
process
involves
active
commitment
all
parties,
including
governments,
medical
health
executives,
citizens.
Sensors,
Год журнала:
2023,
Номер
23(23), С. 9303 - 9303
Опубликована: Ноя. 21, 2023
Over
the
last
decade,
there
has
been
a
large
amount
of
research
on
technology-enhanced
learning
(TEL),
including
exploration
sensor-based
technologies.
This
area
seen
significant
contributions
from
various
conferences,
European
Conference
Technology-Enhanced
Learning
(EC-TEL).
In
this
research,
we
present
comprehensive
analysis
that
aims
to
identify
and
understand
evolving
topics
in
TEL
their
implications
defining
future
education.
To
achieve
this,
use
novel
methodology
combines
text-analytics-driven
topic
social
network
following
an
open
science
approach.
We
collected
corpus
477
papers
decade
EC-TEL
conference
(including
full
short
papers),
parsed
them
automatically,
used
extracted
text
find
main
collaborative
networks
across
papers.
Our
focused
three
objectives:
(1)
Discovering
based
paper
keywords
modeling
using
manuscripts.
(2)
evolution
said
over
ten
years
conference.
(3)
how
authors
have
interacted
perspective.
Specifically,
Python
PdfToText
library
parse
extract
author
corpus.
Moreover,
employed
Gensim
Latent
Dirichlet
Allocation
(LDA)
discover
primary
decade.
Finally,
Gephi
Networkx
libraries
were
create
co-authorship
citation
networks.
findings
provide
valuable
insights
into
latest
trends
developments
educational
technology,
underlining
critical
role
sensor-driven
technologies
leading
innovation
shaping
area.
