Cybercrime Resilience in the Era of Advanced Technologies: Evidence from the Financial Sector of a Developing Country
Computers,
Год журнала:
2025,
Номер
14(2), С. 38 - 38
Опубликована: Янв. 27, 2025
Technological
advancements
have
helped
all
sectors
to
evolve.
This
advancement
has
widened
the
cyberspace
and
attack
surface,
which
led
a
drastic
increase
in
cyberattacks.
Cybersecurity
solutions
also
evolved.
The
is
relatively
slower
developing
countries.
However,
financial
sector
countries
shown
resistance
paper
investigates
reasons
for
this
resistance.
Despite
using
legacy
systems,
banking
Pakistan
demonstrated
research
used
qualitative
approach.
Semi-structured
interviews
were
conducted
with
nine
cybersecurity
experts
illustrate
focused
on
sector,
recognizing
that
industry
particularly
prone
cyberattacks
global
scale.
study
utilised
thematic
analysis
technique
find
factors.
suggests
opportunity
cost
of
lower
surface
like
are
main
losses.
findings
will
encourage
adoption
advanced
technologies
such
as
artificial
intelligence
(AI)
machine
learning
(ML)
countries’
sectors.
Язык: Английский
The Mediating Role of Attitude Towards the Technology in Shaping Artificial Intelligence Usage Among Professionals
Telematics and Informatics Reports,
Год журнала:
2025,
Номер
unknown, С. 100188 - 100188
Опубликована: Фев. 1, 2025
Язык: Английский
ChatGPT-Related Risk Patterns and Students’ Creative Thinking Toward Tourism Statistics Course: Pretest and Posttest Quasi-Experimentation
Journal of Hospitality & Tourism Education,
Год журнала:
2025,
Номер
unknown, С. 1 - 16
Опубликована: Янв. 25, 2025
Язык: Английский
Design and Psychometric Evaluation of the Artificial Intelligence Acceptance and Usage in Research Creativity Scale Among Faculty Members: Insights From the Network Analysis Perspective
European Journal of Education,
Год журнала:
2025,
Номер
60(1)
Опубликована: Янв. 27, 2025
ABSTRACT
The
acceptance
of
artificial
intelligence
(AI)
in
academic
settings,
particularly
the
context
research
creativity,
is
a
growing
area
interest.
This
study
aimed
to
design
and
validate
AI
Acceptance
Research
Creativity
Scale
(AIA&RCS)
among
faculty
members.
exploratory
mixed‐method
was
conducted
720
A
literature
review
participant
interviews
were
qualitative
phase
generate
develop
items.
In
quantitative
phase,
face
validity,
content
construct
convergent
validity
reliability
(internal
consistency
stability)
used.
Exploratory
factor
analysis
(EFA)
indicated
4‐factor
model
scale
with
‘perceived
usefulness
effectiveness
creativity’,
‘ethical
issues
research’,
‘trusted
capabilities’
‘willingness
use
AI’
accounting
for
51.6%
variance.
arrangement
verified
by
confirmatory
(CFA),
fit
indices
that
at
suitable
levels.
Then,
network
took
into
account
four‐factor
structure
AIA&RCS
further.
Similarly,
graph
(EGA)
configuration
AIA&RCS.
25‐item
well‐suited
measuring
innovation
because
its
psychometrics.
Язык: Английский
Artiffical intelligence elements as antecendents of social media consumer engagement and purchase intention
International Communication of Chinese Culture,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 9, 2025
Язык: Английский
Factors influencing Chinese college students’ intention to use AIGC: a study based on the UTAUT model
International Journal of Systems Assurance Engineering and Management,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 1, 2025
Язык: Английский
The data scientist as a mainstay of the tumor board: global implications and opportunities for the global south
Frontiers in Digital Health,
Год журнала:
2025,
Номер
7
Опубликована: Фев. 6, 2025
Tumor
boards
are
multidisciplinary
teams
of
healthcare
professionals
that
working
together
to
encompass
the
full
spectrum
care
around
diagnosing,
planning
treatment,
and
advising
outcomes
for
individual
cancer
patients.
These
typically
consist
oncologists,
radiologists,
pathologists,
geneticists,
surgeons,
nurse
practitioners,
other
palliative
(National
Cancer
Institute,
2024).
create
a
collaborative
space
experts
from
various
disciplines
assess
clinical
factors
patient
circumstances,
ensuring
application
appropriate
standards
personalized
recommendations
National
Comprehensive
Network
(NCCN)
Guidelines
enhance
treatment
met.
Since
no
fits
"textbook"
profile,
oncologists
benefit
discussing
tailored
plans
learning
their
colleagues'
experiences.
When
tumor
functioning
well,
they
can
have
significant
impact
on
(NCCN,
2025).
For
instance,
thoracic
oncology
board
in
Munich,
Germany,
found
90%
met
or
exceeded
standards,
with
nearly
being
implemented
practice
(Walter
et
al,
2023).Tumor
increasingly
used
worldwide,
but
expertise
resources
conducting
still
limited
Global
South.
However,
this
does
not
mean
cannot
be
developing
countries.
A
2020
survey
Southeast
Asia
80.4%
pediatric
solid
units
had
pediatric-trained
specialists,
including
radiation
nuclear
medicine
physicians,
nurses.
This
indicates
already
place
these
specialists
play
critical
role
(Ottman,
2020).
With
implementation
global
south,
data
scientists
further
AI
analytics
improve
decision-making
personalize
care.Advances
big
data,
machine
(ML),
artificial
intelligence
(AI)
provide
more
precise,
evidence-based,
patient-specific
care,
thus,
giving
different
approach
as
how
diagnose,
treat,
manage
patients
(Alowais
2023).
there
is
growing
number
complexity
industry
such
Electronic
Health
Records
(EHRs),
next-generation
genomic
sequencing
(NGS),
advanced
imaging
modalities
like
X-ray
Radiography,
Magnetic
Resonance
Imaging
(MRI),
Computed
Tomography
(CT)
scans.
analyzing
individually
manually,
time-consuming
considerably
impractical.
where
decision
support
systems
(CDSS)
powered
by
ML
put
into
action.
predictive
analysis
disease
progression
prognosis,
based
patients'
drug-drug
interaction
alerts
(Wang
2023;Alowais
As
precision
continue
evolve,
will
rely
data-driven
tools
reduce
errors,
overall
health
(Khalifa
Albadawy,
Data
process
analyze
large
datasets
identify
biomarkers
predict
respond
specific
treatments
(Nardone
In
addition,
algorithms
interpret
radiological
images,
detect
early
signs
cancer,
progression.
becoming
standard
boards,
especially
high-income
countries
(Bi
2019;El
Saghir
2015).For
oncology,
most
commonly
diagnostic
guide
targeted
therapies
Polymerase
Chain
Reaction
(PCR),
fluorescent
situ
hybridization
(FISH),
immunohistochemistry
(IHC)
(Goosens
2015).
high-throughput
(NGS)-based
diagnostics,
which
somatic
mutations
tumors,
proven
clinically
useful
identifying
single-nucleotide
mutations,
insertions,
deletions,
rearrangements
(Kamps
2017).
Thus,
multigene
NGS
testing
oncologist
picture
molecular
profile
utilized
best
option
(Mehta
2020).As
continues
gain
prominence
characterization
cancers
becomes
complex
(Specchia
al.,
2020;Nardone
2024),
incorporating
essential.
bring
ML,
analysis,
bioinformatics,
enabling
make
accurate,
evidence-based
decisions
lead
improved
2024;Rodriguez
Ruiz
2022).
They
synthesizing
diverse
generated
uncovering
actionable
insights,
informing
strategies.
particularly
crucial
shifts
focus
toward
approaches
genetic
characteristics
tumors
(Subrahmanya,
2022).Specifically,
apply
statistical
techniques
survival
clustering,
modeling
uncover
insights
inform
decisions.Their
knowledge
foundation
models,
Generative
Pre-trained
Transformer
(GPT),
Bidirectional
Encoder
Representations
Transformers
(BERT),
memory-augmented
neural
networks
enables
them
extract
valuable
unstructured
medical
records
pathology
reports
2024;Wang
2023).Globally,
trend
towards
integrating
care.
countries,
AI-based
assist
clinicians
interpreting
predicting
outcomes,
optimal
United
States,
example,
institutions
Memorial
Sloan
Kettering
Center
using
tools,
algorithms,
real
time
during
discussions.
integration
varies
across
regions,
some
low-and
middle-income
facing
barriers
adoption
due
lack
infrastructure
(Zuhair
2024).In
States
Europe,
key
members
boards.
at
University
Florida
collaborate
develop
models
(UF
Health,
AI-driven
responses
potential
trials.
Similarly,
work
real-world
integrate
it
decision-making,
each
receives
unique
(Harris
2023).Data-driven
provided
revolutionized
treatment.
By
large-scale
datasets,
driving
suggest
likely
effective
than
(Berger
Mardis,
2018).
Predictive
also
forecast
allowing
tailor
predicted
response.
trial-and-error
nature
efficient
2023).Al
promising
innovation
imaging,
applications
ranging
image
acquisition
processing
reporting,
follow-up
planning,
management.
Given
broad
scope
applications,
anticipated
daily
radiologists
(Pesapane
The
challenge,
however,
lies
AI-powered
equipment
information
training
many
professionals,
radiologists.
preparation
may
contribute
reluctance
adopt
radiology
fields
(Waymel,
2019;Pesapane
Nevertheless,
transformative
advancements
only
occurring
academic
hospitals
highly
facilities,
regions
communities
grappling
greatest
challenges
disparities
(Sitek,
2024).While
made
strides
science
LMICs
face
challenges.
include
computational
infrastructure,
insufficient
access
high-quality
shortage
trained
capable
(Alami
Additionally,
concerns
about
algorithmic
bias
ethical
implications
healthcare,
populations
(Siala
Wang,
Overcoming
require
investment
both
technology
human
capital,
well
development
frameworks
use
settings.In
South,
includes
Asia,
Africa,
Latin
America
Caribbean
(United
Nations
Development
Programme
(UNDP),
2004),
often
hampered
outdated
infrastructure.
higher
rates
late-stage
diagnoses
poorer
compared
(Bamodu
Chung,
parts
Sub-Saharan
Africa
travel
long
distances
leading
delays
diagnosis
(Mwamba
Moreover,
underfunded
latest
advances
Just
Philippines,
main
challenge
difficulty
financial
toxicity
brings
family
(Fernandez
&
Ting,
Thus
despite
national
incorporate
country
(Loong
2023)
very
challenging
day-to-day
practice.
If
cost
were
limiting
factor,
Philippines
would
managing
(Catedral
2020).Data
address
South
leveraging
optimize
resource
allocation
accuracy.
telemedicine
platforms
mobile
(mHealth)
real-time
rural
areas
(Haleem
2021;Akingbola
progression,
high
risk
complications,
prioritize
those
need
(Alowais,
IBM's
Watson
Oncology
(WFO),
an
CDSS
therapy
selection
(Liu
2018),
beneficial
tool
Hence,
track
monitor
responses,
2019).
applied
even
absence
equipment,
help
regions.While
studies
settings
LMICs,
specifically
limited.
Kenya,
screen
cervical
areas,
significantly
reducing
While
Ethiopia,
been
blood
smear
images
diagnose
leukemia
accuracy
(Akingbola
examples
demonstrate
revolutionize
providing
affordable,
scalable
solutions
pressing
Academy
International
(USAID)
has
making
efforts
gap
highlighting
actions
effectively
promote
(USAID,
2022).Transdisciplinarity
emerged
multiple
integrated
tackle
problems
angles.
incorporates
domains
medicine,
science,
social
sciences,
ethics.
pooling
fields,
providers
offer
comprehensive
patients,
(Van
Bewer,
Complex
Hospital
S.G.
Bosco
Turin,
nurses
psychologists,
workers
worked
unmet
needs
innovative
projects
(Clementi
Transdisciplinary
successful
strategy
expediting
emergency
department
(ED)
flow.
Through
collaboration
allied
team
was
able
efficiently,
prompt
delivery
(Innes
2016).
secondary
BRIGHT
Study
chronic
illness
management
after
heart
transplant
revealed
centers
dedicated
achieved
better
(p=0.042)
(Cajita,
Similar
disciplines,
leverage
resources,
project
linking
54
million
electronic
England
(Wood,
2021).
highlight
within
transdisciplinary
sectors.To
must
meet
range
technical,
domain-specific,
interpersonal
requirements.
modeling,
essential,
oncology-related
omic
records.
Candidates
should
hold
graduate-level
degree
discipline
strong
emphasis
statistics
mathematics,
statistics,
physics,
biology,
computer
electrical
engineering,
biomedical
engineering
(BME),
related
fields.
level
ensures
ability
handle
heterogeneous
while
adhering
regulations
similar
Insurance
Portability
Accountability
Act
(HIPAA)
maintain
privacy
confidentiality.A
robust
understanding
terminology
workflows
seamless
communication
professionals.
Furthermore,
excel
translating
findings
employing
visualization
facilitate
disciplines.
Beyond
technical
skills,
abilities
vital
environment
To
ensure
quality
consistency
contributions,
eligibility
regulation
international
professional
bodies.
Lastly,
commitment
continuous
adapt
emerging
innovations
medicine.Insights
study
Fermin
Tan
(2021),
BME
formal
discipline,
importance
formalized
educational
pathways
recognition
healthcare.
research
demonstrated
recognizing
field
achieve
impactful
innovations.
Applying
lessons
emphasizes
structured
education
programs
regulatory
LMIC
contexts.Efforts
standardize
qualifications
competencies
EDISON
Science
Framework
(EDSF),
provides
professionalization
comprising
components
Competence
(CF-DS),
Body
Knowledge
(DS-BoK),
Model
Curriculum
(MC-DS),
Professional
Profiles
(DSPP)
(Demchenko
2017a(Demchenko
,
2017b(Demchenko
2017c(Demchenko
2017d)).
American
Medical
Informatics
Association
(AMIA)
competency-based
accreditation
informatics,
aligns
closely
roles
(Valenta
Computing
Machinery
(ACM)
supports
computing
undergraduate
curricula,
detailing
essential
skills
(ACM,
2021).Country-specific
vary;
skills-based
hiring
under
Executive
Order
14110
practical
over
(US
Office
Personnel
Management
[OPM],
Occupational
Standards
(NOS)
Kingdom
outlines
detailed
performance
criteria
life
sciences
(Unique
Registration
Number
[URN]
COGBIO-05),
applicable
specialized
Standards,
2018).The
scientist
plays
synthesizer
knowledge,
patterns
large,
disparate
domains,
clinical,
genomic,
environmental
(Hassan
Within
do
employ
variety
breadth
contribution
extends
beyond
reinforcement
learning,
Bayesian
networks,
simulation-based
approaches,
others.Reinforcement
type
algorithm
learns
sequences
maximizing
cumulative
rewards,
(Coronato
account
differences
between
classic
RL
following
Markov
assumption
future
state
system
depends
its
current
(Kuznetsov
2010).
suggesting
adaptation
model.
dynamic
strategies
patient's
response
ongoing
treatments.
continuously
adjust
dosages
chemotherapy
minimize
effectiveness
(Eckardt
Tempo,
novel
framework
screening,
context
breast
cancer.
Tempo
policy,
combined
model,
outperforms
practices
detection
adapted
screening
preferences.
It
improves
overscreening
(Yala
allows
time,
adaptive
new
emerges.
tailors
assessments
profiles,
enhancing
precision.Data
probabilistic
graphical
represent
set
variables
conditional
dependencies.
likelihood
observed
data.
setting,
sources-clinical
biomarkers,
history-to
estimate
probabilities
uncertainty
quantifications,
helping
doctors
informed
cases
ambiguity
(Polotskaya
Huehn
al
developed
digital
model
relevant
head
neck
squamous
cell
carcinoma
(HNSCC).
Validation
showed
guides
immunotherapy
decisions,
84%
concordance
(Cohen's
κ
=
0.505,
p
0.009)
when
actual
25
created
physician's
patient.Simulation-based
enable
virtual
scenarios
evaluate
outcomes.
simulating
strategies,
explore
consequences
before
applying
simulations
options,
long-term
effects
profiles
(Nave,
Federov
(2020),
method
optimizing
Treating
Fields
(TTFields)
brain
tumors.
TTFields,
delivered
through
transducer
arrays
skin,
inhibit
growth,
distribution
varying
array
placement,
anatomy,
characteristics.
Incorporating
expected
physician
TTFields
ultimately
improving
outcomes.In
addition
dose
optimization
amount
timing
radiation.
aim
balance
efficacy
minimizing
side
effects,
involve
toxic
agents.
adjusting
dosing
schedules
metabolism
characteristics,
duration
frequency
increase
probability
success
without
compromising
(Bräutigam,
emergence
anti-tumor
complicates
this,
creating
urgent
optimized
dose-schedule
designs
doses
concurrently
single
trial
(Chen
recent
deep
(DL)
led
DL-based
prediction
models.
Unlike
traditional
methods,
DL
automatically
extracts
features
CT,
MRI,
PET
scans
map
values,
guiding
final
distribution.
distributions
anatomical
prescriptions
(Jiang
2024).Multi-omics
another
important
facet
planning.
combine
genomics,
transcriptomics,
proteomics,
metabolomics
tumor.
therapies.
multi-omics
might
reveal
just
mutation
interacts
pathways,
treatments,
targeting
metabolic
aberration
(Babu
Snyder,
Multi-omics
offers
view
volumes
pose
analytical
helps
extracting
omics
advancing
(Li
Cai
al.
(2022),
explored
methods
research,
general-purpose
task-specific
approaches.
benchmarked
five
Cell
Line
Encyclopedia,
assessing
classification,
drug
prediction,
runtime
efficiency.
Their
paper
selecting
encourages
advance
discovery
treatments.Radiomics
involves
quantitative
(e.g.,
scans)
heterogeneity
pathomics
analyzes
histopathological
discernible
pathologist
alone.
image-derived
predictions
select
therapeutic
Like
(2024),
radiopathomics
classify
stage
I,
II,
III
gastric
Other
researchers
prognosis
colorectal
lung
cancers,
2020a(Wang
2020b)).
Radiomics
situations
available,
offering
non-invasive
options
(Gillies
2016;Brancato
.Spatial
biology
technologies,
GeoMx®
(NanoString
Technologies®)
1
CosMx™
2
Visium®
(10x
Genomics®)
3
Xenium™
4
revolutionizing
profiling
spatial
context.
mapping
heterogeneity,
microenvironment,
cell-cell
interactions,
bulk
offer.
transcriptomics
(spTx)
5
6
combining
high-resolution
RNA
profiling,
capturing
cellular
organization
biomarker
localization
tissue
samples
(Cook
HD
7
sub-cellular
resolution,
reconstruction
morphology
expression
(Polanski
2024)
.One
notable
spTx
Despite
faces
intratumoral
(ITH),
tumour
differently
drugs.
Using
spTx,
shows
sensitivity
tumor,
core
periphery.
finds
genetically
identical
cells
depending
location
(Jimenez-Santos
consider
surrounding
microenvironment.
could
addressing
tumor's
complexity,
chances
failure.Causal
focuses
determining
cause-and-effect
relationships,
going
correlation
interventions
Peter-Clark
(PC)
(Spirtes
1993)
latent
Gaussian
causal
(Cai
SHapley
Additive
exPlanations
(SHAP)
Local
Interpretable
Agnostic
Explanation
(LIME)
primarily
explain
correlations
rather
causation
(Ladbury
2022).For
language
(LLM)
impacting
Non
Small
Lung
(NSCLC),
revealing
potentially
unexpected
relationships
smoking
status
having
effect
choice
(Naik
further,
infe
Язык: Английский
AI and education: combination to enhance knowledge
Deleted Journal,
Год журнала:
2024,
Номер
4, С. 37 - 37
Опубликована: Окт. 11, 2024
Artificial
intelligence
(AI)
has
revolutionized
numerous
fields,
education
is
one
of
the
most
benefited.
Technologies
like
Chat
GPT
have
marked
a
before
and
after
in
evolution
AI,
providing
tools
to
automate
repetitive
tasks,
allowing
educators
dedicate
more
time
students.
In
addition
optimizing
resource
management,
AI
personalizes
through
advanced
algorithms
data
analysis,
adapting
resources
methodologies
individual
needs
each
student.
This
facilitates
learning,
promotes
inclusion
offers
effective
education,
especially
for
people
with
disabilities
or
diverse
learning
styles.
this
article,
bibliometric
review
was
carried
out
on
relationship
between
education.
The
essential
requirements
search
were
scientific
texts
published
last
five
years
(2020-2024)
be
found
Scopus
Web
Science
databases,
fundamentally.
opens
new
perspectives
educational
research,
allows
detailed
analysis
large
volumes
can
identify
previously
undetected
areas
improvement
Язык: Английский
Impacting Elements of Metaverse Platforms’ Intentional Use in Cultural Education: Empirical Data Drawn from UTAUT, TTF, and Flow Theory
Applied Sciences,
Год журнала:
2024,
Номер
14(21), С. 9984 - 9984
Опубликована: Окт. 31, 2024
This
study
aims
to
address
the
need
for
design
guidelines
in
developing
a
cultural-heritage-based
metaverse
educational
system.
Using
UTAUT,
TTF
model,
and
Flow
Theory,
theoretical
framework
is
constructed.
Through
qualitative
research
based
on
GT,
three
user
perception
factors—presence,
interactivity,
narrativity—are
introduced
as
external
variables
explore
relationship
between
these
factors
users’
willingness
adopt
cultural
heritage
The
examines
this
from
dual
perspectives
of
technology
acceptance.
A
scale
was
designed
test
model
empirically,
298
valid
responses
were
collected
through
structured
process
involving
GT
coding,
pre-testing,
formal
surveys.
findings
indicate
that
narrativity,
presence
significantly
enhance
flow
experience,
while
such
performance
expectancy,
effort
social
influence,
facilitating
conditions,
technology–task
fit,
positively
influence
intention
Among
these,
fit
emerged
most
influential
factor.
integrated
approach
reduces
subjectivity
bias
criteria
determination,
enhancing
objectivity
precision
system
assessments
making
more
responsive
needs.
Язык: Английский