Life,
Journal Year:
2024,
Volume and Issue:
14(7), P. 833 - 833
Published: June 29, 2024
Cancer
remains
a
significant
global
health
challenge
due
to
its
high
morbidity
and
mortality
rates.
Early
detection
is
essential
for
improving
patient
outcomes,
yet
current
diagnostic
methods
lack
the
sensitivity
specificity
needed
identifying
early-stage
cancers.
Here,
we
explore
potential
of
multi-omics
approaches,
which
integrate
genomic,
transcriptomic,
proteomic,
metabolomic
data,
enhance
early
cancer
detection.
We
highlight
challenges
benefits
data
integration
from
these
diverse
sources
discuss
successful
examples
applications
in
other
fields.
By
leveraging
advanced
technologies,
can
significantly
improve
diagnostics,
leading
better
outcomes
more
personalized
care.
underscore
transformative
approaches
revolutionizing
need
continued
research
clinical
integration.
Cancer Letters,
Journal Year:
2024,
Volume and Issue:
unknown, P. 217350 - 217350
Published: Nov. 1, 2024
Pancreatic
cancer
remains
one
of
the
most
challenging
malignancies
to
treat
due
its
late-stage
diagnosis,
aggressive
progression,
and
high
resistance
existing
therapies.
This
review
examines
latest
advancements
in
early
detection,
therapeutic
strategies,
with
a
focus
on
emerging
biomarkers,
tumor
microenvironment
(TME)
modulation,
integration
artificial
intelligence
(AI)
data
analysis.
We
highlight
promising
including
microRNAs
(miRNAs)
circulating
DNA
(ctDNA),
that
offer
enhanced
sensitivity
specificity
for
early-stage
diagnosis
when
combined
multi-omics
panels.
A
detailed
analysis
TME
reveals
how
components
such
as
cancer-associated
fibroblasts
(CAFs),
immune
cells,
extracellular
matrix
(ECM)
contribute
therapy
by
creating
immunosuppressive
barriers.
also
discuss
interventions
target
these
components,
aiming
improve
drug
delivery
overcome
evasion.
Furthermore,
AI-driven
analyses
are
explored
their
potential
interpret
complex
data,
enabling
personalized
treatment
strategies
real-time
monitoring
response.
conclude
identifying
key
areas
future
research,
clinical
validation
regulatory
frameworks
AI
applications,
equitable
access
innovative
comprehensive
approach
underscores
need
integrated,
outcomes
pancreatic
cancer.
Public Health Nursing,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 4, 2024
ABSTRACT
Background
Artificial
intelligence
now
encompasses
technologies
like
machine
learning,
natural
language
processing,
and
robotics,
allowing
machines
to
undertake
complex
tasks
traditionally
done
by
humans.
AI's
application
in
healthcare
has
led
advancements
diagnostic
tools,
predictive
analytics,
surgical
precision.
Aim
This
comprehensive
review
aims
explore
the
transformative
impact
of
AI
across
diverse
domains,
highlighting
its
applications,
advancements,
challenges,
contributions
enhancing
patient
care.
Methodology
A
literature
search
was
conducted
multiple
databases,
covering
publications
from
2014
2024.
Keywords
related
applications
were
used
gather
data,
focusing
on
studies
exploring
role
medical
specialties.
Results
demonstrated
substantial
benefits
various
fields
medicine.
In
cardiology,
it
aids
automated
image
interpretation,
risk
prediction,
management
cardiovascular
diseases.
oncology,
enhances
cancer
detection,
treatment
planning,
personalized
drug
selection.
Radiology
improved
analysis
accuracy,
while
critical
care
sees
triage
resource
optimization.
integration
into
pediatrics,
surgery,
public
health,
neurology,
pathology,
mental
health
similarly
shown
significant
improvements
precision,
treatment,
overall
The
implementation
low‐resource
settings
been
particularly
impactful,
access
advanced
tools
treatments.
Conclusion
is
rapidly
changing
industry
greatly
increasing
accuracy
diagnoses,
streamlining
plans,
improving
outcomes
a
variety
specializations.
underscores
potential,
early
disease
detection
ability
augment
delivery,
resource‐limited
settings.
Journal of Materials Chemistry B,
Journal Year:
2024,
Volume and Issue:
12(19), P. 4584 - 4612
Published: Jan. 1, 2024
Recent
advancements
pertaining
to
the
application
of
3D,
4D,
5D,
and
6D
bioprinting
in
cancer
research
are
discussed,
focusing
on
important
challenges
future
perspectives.
BJC Reports,
Journal Year:
2025,
Volume and Issue:
3(1)
Published: April 1, 2025
The
field
of
genomic
medicine
produces
large
datasets,
which
need
to
be
rapidly
analysed
produce
clinically
actionable
insights
in
cancer
care.
Artificial
intelligence
thrives
on
data,
processing
and
learning
from
datasets
with
a
degree
accuracy
efficiency
that
traditional
computing
algorithms
can
not
achieve.
Based
patient's
genome
sequence,
AI
could
allow
earlier
detection
cancer,
inform
personalised
treatment
plans
provide
into
prognostication.
However,
this
valuable
tool
is
met
skepticism,
stakeholders
concerned
over
data
security,
liability
for
AI's
mistakes
due
hallucination
the
threat
clinical
jobs.
This
review
highlights
both
benefits
potential
problems
using
care,
aim
lessen
knowledge
gap
between
clinicians
scientists
facilitate
future
deployment
Bioengineering Studies,
Journal Year:
2024,
Volume and Issue:
5(1), P. 1 - 14
Published: July 30, 2024
Breast
cancer
is
one
of
the
most
common
types
among
women
worldwide,
therefore
an
early
and
precise
process
diagnostics
plays
important
role
in
improving
prognosis
outcome
treatment.
The
application
artificial
intelligence
(AI)
allows
faster
more
analysis
medical
imaging,
which
contributes
to
detection
tumors
lowers
number
false-negative
results.
This
review
article
analyzed
60
scientific
papers
using
recent
findings
about
this
topic,
searched
for
AI
implementation
breast
research
how
may
improve
overall
survival
outcomes
patients.
