International Journal of Environmental Research and Public Health,
Journal Year:
2023,
Volume and Issue:
20(13), P. 6216 - 6216
Published: June 24, 2023
In
this
study,
machine
learning
models
were
implemented
to
predict
the
classification
of
coastal
waters
in
region
Eastern
Macedonia
and
Thrace
(EMT)
concerning
Escherichia
coli
(E.
coli)
concentration
weather
variables
framework
Directive
2006/7/EC.
Six
sampling
stations
EMT,
located
on
beaches
regional
units
Kavala,
Xanthi,
Rhodopi,
Evros,
Thasos
Samothraki,
selected.
All
1039
samples
collected
from
May
September
within
a
14-year
follow-up
period
(2009–2021).
The
parameters
acquired
nearby
meteorological
stations.
analysed
according
ISO
9308-1
for
detection
enumeration
E.
coli.
vast
majority
fall
into
category
1
(Excellent),
which
is
mark
high
quality
EMT.
experimental
results
disclose,
additionally,
that
two-class
classifiers,
namely
Decision
Forest,
Jungle
Boosted
Tree,
achieved
Accuracy
scores
over
99%.
addition,
comparing
our
performance
metrics
with
those
other
researchers,
diversity
observed
using
algorithms
water
prediction,
such
as
Artificial
Neural
Networks
Bayesian
Belief
demonstrating
satisfactory
results.
Machine
approaches
can
provide
critical
information
about
dynamic
contamination
and,
concurrently,
consider
classification.
Chaos Theory and Applications,
Journal Year:
2024,
Volume and Issue:
6(1), P. 1 - 12
Published: March 5, 2024
During
the
nineties,
Rössler’s
have
reported
in
their
famous
book
“Chaos
Physiology,”
that
“physiology
is
mother
of
Chaos.”
Moreover,
several
researchers
proved
Chaos
a
generic
characteristic
systems
physiology.
In
context
disease,
like
for
example
growth
cancer
cell
populations,
often
refers
to
irregular
and
unpredictable
patterns.
such
cases,
signatures
can
be
used
prove
existence
some
pathologies.
However,
other
physiological
behaviors,
form
order
disguised
as
disorder
signature
healthy
functions.
This
case
human
brain
behavior.
As
boundary
between
health
disease
not
always
clear-cut
chaotic
physiology,
conditions
may
involve
transitions
ordered
states.
Understanding
these
identifying
critical
points
crucial
predicting
Healthy
vs.
pathological
Chaos.
Using
recent
advances
dynamics,
this
survey
paper
tries
answer
question:
when
sign
or
disease?
Energies,
Journal Year:
2024,
Volume and Issue:
17(13), P. 3267 - 3267
Published: July 3, 2024
Chemical
vapor
deposition
(CVD)
is
a
vital
process
for
deposit
of
thin
films
various
materials
with
precise
control
over
the
thickness,
composition,
and
properties.
Understanding
mechanisms
heat
mass
transfer
during
CVD
essential
optimizing
parameters
ensuring
high-quality
film
deposition.
This
review
provides
an
overview
recent
advancements
in
modeling
chemical
processes.
It
explores
innovative
techniques,
research
findings,
emerging
applications,
challenges
field.
Additionally,
it
discusses
future
directions
potential
areas
further
advancement
modeling.
International Journal of Surgery,
Journal Year:
2024,
Volume and Issue:
110(11), P. 7202 - 7214
Published: July 24, 2024
Infective
endocarditis
(IE)
is
a
severe
infection
of
the
inner
lining
heart,
known
as
endocardium.
It
characterized
by
range
symptoms
and
has
complicated
pattern
occurrence,
leading
to
significant
number
deaths.
IE
poses
diagnostic
treatment
difficulties.
This
evaluation
examines
utilization
artificial
intelligence
(AI)
machine
learning
(ML)
models
in
addressing
information
extraction
management.
focuses
on
most
recent
advancements
possible
applications.
Through
this
paper,
we
observe
that
AI/ML
can
significantly
enhance
outperform
traditional
methods
more
accurate
risk
stratification,
personalized
therapies
well
real-time
monitoring
facilities.
For
example,
early
postsurgical
mortality
prediction
like
SYSUPMIE
achieved
'very
good'
area
under
curve
(AUROC)
values
exceeding
0.81.
Additionally,
improved
accuracy
for
prosthetic
valve
endocarditis,
with
PET-ML
increasing
sensitivity
from
59%
72%
when
integrated
into
ESC
criteria
reaching
high
specificity
83%.
Furthermore,
inflammatory
biomarkers
such
IL-15
CCL4
have
been
identified
predictive
markers,
showing
91%
forecasting
mortality,
identifying
high-risk
patients
specific
CRP,
IL-15,
levels.
Even
simpler
ML
models,
Naïve
Bayes,
demonstrated
an
excellent
92.30%
death
rate
following
valvular
surgery
patients.
review
provides
vital
assessment
advantages
disadvantages
better-quality
decision
support
approaches
adaptive
response
systems
one
hand,
data
privacy
threats
or
ethical
concerns
other
hand.
In
conclusion,
Al
must
continue,
through
multi-centric
validated
research,
advance
cardiovascular
medicine,
overcome
implementation
challenges
boost
patient
outcomes
healthcare
delivery.
International Journal of Environmental Research and Public Health,
Journal Year:
2023,
Volume and Issue:
20(13), P. 6216 - 6216
Published: June 24, 2023
In
this
study,
machine
learning
models
were
implemented
to
predict
the
classification
of
coastal
waters
in
region
Eastern
Macedonia
and
Thrace
(EMT)
concerning
Escherichia
coli
(E.
coli)
concentration
weather
variables
framework
Directive
2006/7/EC.
Six
sampling
stations
EMT,
located
on
beaches
regional
units
Kavala,
Xanthi,
Rhodopi,
Evros,
Thasos
Samothraki,
selected.
All
1039
samples
collected
from
May
September
within
a
14-year
follow-up
period
(2009–2021).
The
parameters
acquired
nearby
meteorological
stations.
analysed
according
ISO
9308-1
for
detection
enumeration
E.
coli.
vast
majority
fall
into
category
1
(Excellent),
which
is
mark
high
quality
EMT.
experimental
results
disclose,
additionally,
that
two-class
classifiers,
namely
Decision
Forest,
Jungle
Boosted
Tree,
achieved
Accuracy
scores
over
99%.
addition,
comparing
our
performance
metrics
with
those
other
researchers,
diversity
observed
using
algorithms
water
prediction,
such
as
Artificial
Neural
Networks
Bayesian
Belief
demonstrating
satisfactory
results.
Machine
approaches
can
provide
critical
information
about
dynamic
contamination
and,
concurrently,
consider
classification.
