Prediction of Lymph Node Metastasis in Endometrial Cancer Based on Color Doppler Ultrasound Radiomics
Academic Radiology,
Год журнала:
2024,
Номер
31(11), С. 4499 - 4508
Опубликована: Сен. 3, 2024
Язык: Английский
Treatments and cancer: implications for radiologists
Frontiers in Immunology,
Год журнала:
2025,
Номер
16
Опубликована: Апрель 16, 2025
This
review
highlights
the
critical
role
of
radiologists
in
personalized
cancer
treatment,
focusing
on
evaluation
treatment
outcomes
using
imaging
tools
like
Computed
Tomography
(CT),
Magnetic
Resonance
Imaging
(MRI),
and
Ultrasound.
Radiologists
assess
effectiveness
complications
therapies
such
as
chemotherapy,
immunotherapy,
ablative
treatments.
Understanding
mechanisms
consistent
protocols
are
essential
for
accurate
evaluation,
especially
managing
complex
cases
liver
cancer.
Collaboration
between
oncologists
is
key
to
optimizing
patient
through
precise
assessments.
Язык: Английский
CLEAR guideline for radiomics: Early insights into current reporting practices endorsed by EuSoMII
European Journal of Radiology,
Год журнала:
2024,
Номер
181, С. 111788 - 111788
Опубликована: Окт. 14, 2024
Язык: Английский
Machine learning to predict radiomics models of classical trigeminal neuralgia response to percutaneous balloon compression treatment
Ji Wu,
Chengjian Qin,
Yixuan Zhou
и другие.
Frontiers in Neurology,
Год журнала:
2024,
Номер
15
Опубликована: Ноя. 27, 2024
Classic
trigeminal
neuralgia
(CTN)
seriously
affects
patients'
quality
of
life.
Percutaneous
balloon
compression
(PBC)
is
a
surgical
program
for
treating
neuralgia.
But
some
patients
are
ineffective
or
relapse
after
treatment.
The
aim
to
use
machine
learning
construct
clinical
imaging
models
predict
treatment
(PBC).
Язык: Английский
Identification and validation of cigarette smoking-related genes in predicting prostate cancer development through bioinformatic analysis and experiments
Discover Oncology,
Год журнала:
2024,
Номер
15(1)
Опубликована: Дек. 3, 2024
The
morbidity
and
mortality
rates
of
prostate
cancer
(PCa)
are
high
among
elderly
men
worldwide.
Several
factors,
such
as
heredity,
obesity,
environment
associated
with
the
occurrence
PCa.
Cigarette
smoking,
which
is
also
an
important
factor
in
development
PCa,
can
lead
to
genetic
alterations
consequently
promote
PCa
development.
However,
smoking-induced
unclear.
This
study
aimed
identify
potential
smoking-related
genes
differentially
expressed
(DEGs)
were
identified
using
Gene
Expression
Omnibus
(GEO)
included
lots
datasets.
DEGs
subjected
protein–protein
interaction
(PPI)
network
analysis
hub
genes.
pathways
these
enriched
identified.
Cancer
Genome
Atlas
(TCGA)
dataset
was
used
examine
expression
samples
estimate
their
value
predicting
tumor
progression
prognosis.
In
total,
110
got
from
GSE68135
microarray
data
patients
smoking
or
not
14
key
PPI
network.
following
seven
altered
TCGA
patients:
EWSR1,
SRSF6,
COL6A3,
FBLN1,
DCN,
CYP2J2,
PLA2G2A.
CYP2J2
influenced
progression.
Additionally,
EWSR1
disease-free
survival.
logistic
regression
model,
exhibited
highest
risk
scores,
gene
for
We
found
one
genes:
truly
upregulated
clinical
cells
invasion
proliferation.
function
involved
Язык: Английский