Environmental Toxicology and Chemistry,
Journal Year:
2025,
Volume and Issue:
44(2), P. 306 - 317
Published: Jan. 6, 2025
Histological
evaluations
of
tissues
are
commonly
used
in
environmental
monitoring
studies
to
assess
the
health
and
fitness
status
populations
or
even
whole
ecosystems.
Although
traditional
histology
can
be
cost-effective,
there
is
a
shortage
proficient
histopathologists
results
often
subjective
between
operators,
leading
variance.
Digital
pathology
powerful
diagnostic
tool
that
has
already
significantly
transformed
research
human
but
rarely
been
applied
studies.
analyses
slide
images
introduce
possibilities
highly
standardized
histopathological
evaluations,
as
well
use
artificial
intelligence
for
novel
analyses.
Furthermore,
incorporation
digital
into
using
bioindicator
species
groups
such
bivalves
fish
greatly
improve
accuracy,
reproducibility,
efficiency
This
review
aims
readers
how
it
includes
guidelines
sample
preparation,
potential
sources
error,
comparisons
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: Oct. 11, 2023
Current
diagnosis
of
glioma
types
requires
combining
both
histological
features
and
molecular
characteristics,
which
is
an
expensive
time-consuming
procedure.
Determining
the
tumor
directly
from
whole-slide
images
(WSIs)
great
value
for
diagnosis.
This
study
presents
integrated
model
automatic
classification
diffuse
gliomas
annotation-free
standard
WSIs.
Our
developed
on
a
training
cohort
(n
=
1362)
validation
340),
tested
internal
testing
289)
two
external
cohorts
305
328,
respectively).
The
can
learn
imaging
containing
pathological
morphology
underlying
biological
clues
to
achieve
achieves
high
performance
with
area
under
receiver
operator
curve
all
above
0.90
in
classifying
major
types,
identifying
grades
within
type,
especially
distinguishing
genotypes
shared
features.
has
potential
be
used
clinical
scenarios
automated
unbiased
adult-type
gliomas.
Annual Review of Cancer Biology,
Journal Year:
2023,
Volume and Issue:
7(1), P. 57 - 71
Published: Jan. 17, 2023
Histopathology
plays
a
fundamental
role
in
the
diagnosis
and
subtyping
of
solid
tumors
has
become
cornerstone
modern
precision
oncology.
Histopathological
evaluation
is
typically
performed
manually
by
expert
pathologists
due
to
complexity
visual
data.
However,
last
ten
years,
new
artificial
intelligence
(AI)
methods
have
made
it
possible
train
computers
perform
tasks
with
high
performance,
reaching
similar
levels
as
experts
some
applications.
In
cancer
histopathology,
these
AI
tools
could
help
automate
repetitive
tasks,
making
more
efficient
use
pathologists’
time.
research
studies,
been
shown
an
astounding
ability
predict
genetic
alterations
identify
prognostic
predictive
biomarkers
directly
from
routine
tissue
slides.
Here,
we
give
overview
recent
applications
computational
pathology,
focusing
on
for
that
be
pivotal
identifying
clinical
better
treatment
decisions.
Environmental Toxicology and Chemistry,
Journal Year:
2025,
Volume and Issue:
44(2), P. 306 - 317
Published: Jan. 6, 2025
Histological
evaluations
of
tissues
are
commonly
used
in
environmental
monitoring
studies
to
assess
the
health
and
fitness
status
populations
or
even
whole
ecosystems.
Although
traditional
histology
can
be
cost-effective,
there
is
a
shortage
proficient
histopathologists
results
often
subjective
between
operators,
leading
variance.
Digital
pathology
powerful
diagnostic
tool
that
has
already
significantly
transformed
research
human
but
rarely
been
applied
studies.
analyses
slide
images
introduce
possibilities
highly
standardized
histopathological
evaluations,
as
well
use
artificial
intelligence
for
novel
analyses.
Furthermore,
incorporation
digital
into
using
bioindicator
species
groups
such
bivalves
fish
greatly
improve
accuracy,
reproducibility,
efficiency
This
review
aims
readers
how
it
includes
guidelines
sample
preparation,
potential
sources
error,
comparisons
