Research Square (Research Square),
Journal Year:
2023,
Volume and Issue:
unknown
Published: Sept. 15, 2023
Abstract
Text
mining
can
be
used
for
various
biological
and
medical
purposes.
In
this
work,
we
have
text
to
analyze
papers
related
Alzheimer's,
Asthma,
Cancer,
Diabetes,
Fabry,
syndrome
diseases
using
their
abstracts
extracting
from
the
gene
those
diseases.
case,
data
set
collected
sources
was
generated
manually
in
pilot
study.
The
articles
searched
through
PubMed,
Web
of
Science,
Medline.
Extremely
Boosted
Neural
Network
is
a
new
machine
learning
(ML)
algorithm
that
has
been
developed
recently
train
optimization
technique
integrate
tree-based
models
with
networks
(NN).
paper,
an
extremely
boosted
neural
network
utilized
as
novel
application
analysis
extract
information
about
We
benchmark
proposed
model
17
other
ML
models,
achieving
98%
accuracy.
This
significant
improvement
given
most
techniques
received
less
than
97%.
Research Square (Research Square),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Oct. 30, 2024
Abstract
Motor
bearing
fault
detection
(MBFD)
is
vital
for
ensuring
the
reliability
and
efficiency
of
industrial
machinery.
Identifying
faults
early
can
prevent
system
breakdowns,
reduce
maintenance
costs,
minimize
downtime.
This
paper
presents
an
advanced
MBFD
using
deep
learning,
integrating
multiple
training
approaches:
supervised,
semi-supervised,
unsupervised
learning
to
improve
classification
accuracy.
A
novel
double-loss
function
further
enhances
model’s
performance
by
refining
feature
extraction
from
vibration
signals.
Our
approach
rigorously
tested
on
well-known
datasets:
American
Society
Mechanical
Failure
Prevention
Technology
(MFPT),
Case
Western
Reserve
University
Bearing
Data
Center
(CWRU),
Paderborn
University's
Condition
Monitoring
Damage
in
Electromechanical
Drive
Systems
(PU).
Results
indicate
that
proposed
method
outperforms
traditional
machine
models,
achieving
high
accuracy
across
all
datasets.
These
findings
underline
potential
applying
MBFD,
providing
a
robust
solution
predictive
settings
supporting
proactive
management
machinery
health.
2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON),
Journal Year:
2023,
Volume and Issue:
unknown, P. 169 - 173
Published: Dec. 1, 2023
Predicting
hypertension
accurately
is
essential
for
early
intervention
and
effective
disease
management.
In
recent
years,
machine
learning
techniques
have
attracted
considerable
interest
their
potential
to
predict
diagnose
a
variety
of
medical
conditions,
including
hypertension.
The
purpose
this
article
provide
an
insight
into
how
models
are
used
hypertension,
emphasizing
the
methodologies
employed,
performance
metrics,
difficulties
encountered.
article,
properly
analyze
disease,
symptoms
investigations
taken
consideration
pre-process
features.
After
pre-processing,
feature
scaling
applied
optimize
prediction
results.
Further,
learning-based
classify
determine
whether
person
has
issues
or
not.
Based
on
our
analysis,
we
concluded
that
random
forest
KNN
detect
Research Square (Research Square),
Journal Year:
2023,
Volume and Issue:
unknown
Published: Sept. 15, 2023
Abstract
Text
mining
can
be
used
for
various
biological
and
medical
purposes.
In
this
work,
we
have
text
to
analyze
papers
related
Alzheimer's,
Asthma,
Cancer,
Diabetes,
Fabry,
syndrome
diseases
using
their
abstracts
extracting
from
the
gene
those
diseases.
case,
data
set
collected
sources
was
generated
manually
in
pilot
study.
The
articles
searched
through
PubMed,
Web
of
Science,
Medline.
Extremely
Boosted
Neural
Network
is
a
new
machine
learning
(ML)
algorithm
that
has
been
developed
recently
train
optimization
technique
integrate
tree-based
models
with
networks
(NN).
paper,
an
extremely
boosted
neural
network
utilized
as
novel
application
analysis
extract
information
about
We
benchmark
proposed
model
17
other
ML
models,
achieving
98%
accuracy.
This
significant
improvement
given
most
techniques
received
less
than
97%.
