Cell Reports Physical Science,
Год журнала:
2022,
Номер
3(11), С. 101149 - 101149
Опубликована: Ноя. 1, 2022
The
capacity
of
machine-learning
methods
to
handle
large
and
complex
datasets
makes
them
suitable
for
applications
in
precision
medicine.
Current
automate
data
analysis
predict
physiological
outcomes
patients
with
various
types
clinical
inform
treatment
strategies.
In
this
perspective,
we
propose
ways
which
machine
learning
can
be
leveraged
even
further
advance
optimizing
patient
treatment.
Namely,
used
expand
feedback
control
direct
the
response
biological
systems
predictably
automatically.
This
paves
way
highly
sophisticated
treatments
that
continuously
adapt
an
individual
patient's
response.
elements
improved
using
include
sensor
analysis,
modeling,
reconfiguring
algorithm
"on
fly."
We
discuss
challenges
unique
analysis/control
systems,
existing
work,
areas
remain
underdeveloped.
International Journal of Computational and Experimental Science and Engineering,
Год журнала:
2024,
Номер
10(4)
Опубликована: Ноя. 29, 2024
Alzheimer's
Disease
(AD)
is
a
major
global
health
concern.
The
research
focuses
on
early
and
accurate
diagnosis
of
AD
for
its
effective
treatment
management.
This
study
presents
novel
Machine
Learning
(ML)
approach
utilizing
PyCaret
SHAP
interpretable
prediction.
employs
span
classification
algorithms
the
identifies
best
model.
value
determines
contribution
individual
features
final
prediction
thereby
enhancing
model’s
interpretability.
feature
selection
using
improves
overall
performance
proposed
XAI
framework
clinical
decision
making
patient
care
by
providing
reliable
transparent
method
detection.
Mobile Information Systems,
Год журнала:
2022,
Номер
2022, С. 1 - 7
Опубликована: Июнь 17, 2022
Cancer
is
a
disease
caused
by
uncontrollable
cell
growth.
The
constant
subject
of
concern
due
to
unavailability
treatment
at
severe
level.
Patients
who
have
suffered
from
the
chance
getting
saved
if
this
fatal
illness
identified
in
beginning
stage.
survival
will
be
very
low
it
detected
final
stage
cancer.
As
patients
could
not
survive
their
last
stage,
cure
disease,
an
early
diagnosis
key
issue
and
vital.
For
classification
cancer,
Gaussian
Naïve
Bayes
implemented
work.
By
exerting
on
two
datasets,
algorithm
tested,
which
Wisconsin
Breast
Dataset
(WBCD)
considered
as
earliest
one
next
Lung
Dataset.
assessment
result
suggested
attained
90%
accuracy
prediction
lung
predicting
breast
98%.
Journal of Cloud Computing Advances Systems and Applications,
Год журнала:
2022,
Номер
11(1)
Опубликована: Июль 28, 2022
Abstract
Blockchain
is
the
latest
boon
in
world
which
handles
mainly
banking
and
finance.
The
blockchain
also
used
healthcare
management
system
for
effective
maintenance
of
electronic
health
medical
records.
technology
ensures
security,
privacy,
immutability.
Federated
Learning
a
revolutionary
learning
technique
deep
learning,
supports
from
distributed
environment.
This
work
proposes
framework
by
integrating
Deep
order
to
provide
tailored
recommendation
system.
focuses
on
two
modules
blockchain-based
storage
records,
where
uses
Hyperledger
fabric
capable
continuously
monitoring
tracking
updates
Electronic
Health
Records
cloud
server.
In
second
module,
LightGBM
N-Gram
models
are
collaborative
module
recommend
treatment
patient’s
cloud-based
database
after
analyzing
EHR.
shows
good
accuracy.
Several
metrics
like
precision,
recall,
F1
scores
measured
showing
its
utilization
security.
Diagnostics,
Год журнала:
2022,
Номер
12(12), С. 2975 - 2975
Опубликована: Ноя. 28, 2022
Alzheimer’s
disease
(AD)
is
a
polygenic
multifactorial
neurodegenerative
that,
after
decades
of
research
and
development,
still
without
cure.
There
are
some
symptomatic
treatments
to
manage
the
psychological
symptoms
but
none
these
drugs
can
halt
progression.
Additionally,
over
last
few
years,
many
anti-AD
failed
in
late
stages
clinical
trials
hypotheses
surfaced
explain
failures,
including
lack
clear
understanding
pathways
processes.
Recently,
different
epigenetic
factors
have
been
implicated
AD
pathogenesis;
thus,
they
could
serve
as
promising
diagnostic
biomarkers.
network
biology
approaches
suggested
effective
tools
study
on
systems
level
discover
multi-target-directed
ligands
novel
for
AD.
Herein,
we
provide
comprehensive
review
pathophysiology
better
pathogenesis
decipher
role
genetic
development
We
also
an
overview
biomarkers
drug
targets
suggest
new
identifying
drugs.
posit
that
application
machine
learning
artificial
intelligence
mining
multi-omics
data
will
facilitate
biomarker
discovery
efforts
lead
individualized
anti-Alzheimer
treatments.
Cell Reports Physical Science,
Год журнала:
2022,
Номер
3(11), С. 101149 - 101149
Опубликована: Ноя. 1, 2022
The
capacity
of
machine-learning
methods
to
handle
large
and
complex
datasets
makes
them
suitable
for
applications
in
precision
medicine.
Current
automate
data
analysis
predict
physiological
outcomes
patients
with
various
types
clinical
inform
treatment
strategies.
In
this
perspective,
we
propose
ways
which
machine
learning
can
be
leveraged
even
further
advance
optimizing
patient
treatment.
Namely,
used
expand
feedback
control
direct
the
response
biological
systems
predictably
automatically.
This
paves
way
highly
sophisticated
treatments
that
continuously
adapt
an
individual
patient's
response.
elements
improved
using
include
sensor
analysis,
modeling,
reconfiguring
algorithm
"on
fly."
We
discuss
challenges
unique
analysis/control
systems,
existing
work,
areas
remain
underdeveloped.
