Advances in information security, privacy, and ethics book series,
Journal Year:
2023,
Volume and Issue:
unknown, P. 120 - 142
Published: June 23, 2023
The
spread
of
the
COVID-19
pandemic
made
us
rethink
need
for
integrating
modern
scientific
algorithms
in
decision
support
as
well
medical
systems.
This
chapter
focuses
on
on-going
efforts
throughout
world
tackling
with
use
artificial
intelligence
and
machine
learning
algorithms.
also
compiles
various
internationally
providing
solution
to
this
disease.
examples
like
neural
network,
fuzzy
clustering,
vector
machines
both
disease
recognition
aid
have
been
stated.
Finally,
reiterates
developing
even
more
advanced
prediction
systems
case
future
outbreaks
due
ever
mutating
microorganisms
other
lifestyle
problems.
More
than
just
governmental
endeavors,
prudent
handling
any
emergency
health
situation
requires
awareness
self-discipline
exercised
by
inhabitants
country.
Journal of Personalized Medicine,
Journal Year:
2023,
Volume and Issue:
13(6), P. 951 - 951
Published: June 5, 2023
Artificial
intelligence
(AI)
applications
have
transformed
healthcare.
This
study
is
based
on
a
general
literature
review
uncovering
the
role
of
AI
in
healthcare
and
focuses
following
key
aspects:
(i)
medical
imaging
diagnostics,
(ii)
virtual
patient
care,
(iii)
research
drug
discovery,
(iv)
engagement
compliance,
(v)
rehabilitation,
(vi)
other
administrative
applications.
The
impact
observed
detecting
clinical
conditions
diagnostic
services,
controlling
outbreak
coronavirus
disease
2019
(COVID-19)
with
early
diagnosis,
providing
care
using
AI-powered
tools,
managing
electronic
health
records,
augmenting
compliance
treatment
plan,
reducing
workload
professionals
(HCPs),
discovering
new
drugs
vaccines,
spotting
prescription
errors,
extensive
data
storage
analysis,
technology-assisted
rehabilitation.
Nevertheless,
this
science
pitch
meets
several
technical,
ethical,
social
challenges,
including
privacy,
safety,
right
to
decide
try,
costs,
information
consent,
access,
efficacy,
while
integrating
into
governance
crucial
for
safety
accountability
raising
HCPs'
belief
enhancing
acceptance
boosting
significant
consequences.
Effective
prerequisite
precisely
address
regulatory,
trust
issues
advancing
implementation
AI.
Since
COVID-19
hit
global
system,
concept
has
created
revolution
healthcare,
such
an
uprising
could
be
another
step
forward
meet
future
needs.
Heliyon,
Journal Year:
2024,
Volume and Issue:
10(4), P. e26297 - e26297
Published: Feb. 1, 2024
Over
the
past
decade,
there
has
been
a
notable
surge
in
AI-driven
research,
specifically
geared
toward
enhancing
crucial
clinical
processes
and
outcomes.
The
potential
of
AI-powered
decision
support
systems
to
streamline
workflows,
assist
diagnostics,
enable
personalized
treatment
is
increasingly
evident.
Nevertheless,
introduction
these
cutting-edge
solutions
poses
substantial
challenges
care
environments,
necessitating
thorough
exploration
ethical,
legal,
regulatory
considerations.
A
robust
governance
framework
imperative
foster
acceptance
successful
implementation
AI
healthcare.
This
article
delves
deep
into
critical
ethical
concerns
entangled
with
deployment
practice.
It
not
only
provides
comprehensive
overview
role
technologies
but
also
offers
an
insightful
perspective
on
challenges,
making
pioneering
contribution
field.
research
aims
address
current
digital
healthcare
by
presenting
valuable
recommendations
for
all
stakeholders
eager
advance
development
innovative
systems.
EAI Endorsed Transactions on Pervasive Health and Technology,
Journal Year:
2024,
Volume and Issue:
10
Published: Feb. 21, 2024
INTRODUCTION:
The
2019
COVID-19
pandemic
outbreak
triggered
a
previously
unseen
global
health
crisis
demanding
accurate
diagnostic
solutions.
Artificial
Intelligence
has
emerged
as
promising
technology
for
diagnosis,
offering
rapid
and
reliable
analysis
of
medical
data.
OBJECTIVES:
This
research
paper
presents
comprehensive
review
various
artificial
intelligence
methods
applied
the
aiming
to
assess
their
effectiveness
in
identifying
cases,
predicting
disease
progression
differentiating
from
other
respiratory
diseases.
METHODS:
study
covers
wide
range
with
application
analysing
diverse
data
sources
like
chest
x-rays,
CT
scans,
clinical
records
genomic
sequences.
also
explores
challenges
limitations
implementing
AI
-based
tools,
including
availability
ethical
considerations.
CONCLUSION:
Leveraging
AI’s
potential
healthcare
can
significantly
enhance
efficiency
management
evolves.
Abstract
With
the
threat
of
increasing
SARS‐CoV‐2
cases
looming
in
front
us
and
no
effective
safest
vaccine
available
to
curb
this
pandemic
disease
due
its
sprouting
variants,
many
countries
have
undergone
a
lockdown
2.0
or
planning
3.0.
This
has
upstretched
an
unprecedented
demand
develop
rapid,
sensitive,
highly
selective
diagnostic
devices
that
can
quickly
detect
coronavirus
(COVID‐19).
Traditional
techniques
like
polymerase
chain
reaction
proven
be
time‐inefficient,
expensive,
labor
intensive,
impracticable
remote
settings.
shifts
attention
alternative
biosensing
successfully
used
sense
COVID‐19
infection
spread
cases.
Among
these,
nanomaterial‐based
biosensors
hold
immense
potential
for
rapid
detection
because
their
noninvasive
susceptible,
as
well
properties
give
real‐time
results
at
economical
cost.
These
mass
understand
progression
better‐suited
therapies.
review
provides
overview
existing
diagnostics.
Novel
employing
different
mechanisms
are
also
highlighted
sections
review.
Practical
tools
required
such
make
them
reliable
portable
been
discussed
article.
Finally,
is
concluded
by
presenting
current
challenges
future
perspectives
European Journal of Radiology Open,
Journal Year:
2022,
Volume and Issue:
9, P. 100438 - 100438
Published: Jan. 1, 2022
When
diagnosing
Coronavirus
disease
2019(COVID-19),
radiologists
cannot
make
an
accurate
judgments
because
the
image
characteristics
of
COVID-19
and
other
pneumonia
are
similar.
As
machine
learning
advances,
artificial
intelligence(AI)
models
show
promise
in
pneumonias.
We
performed
a
systematic
review
meta-analysis
to
assess
diagnostic
accuracy
methodological
quality
models.
Journal of Clinical Laboratory Analysis,
Journal Year:
2023,
Volume and Issue:
37(6)
Published: March 1, 2023
Decision
trees
are
efficient
and
reliable
decision-making
algorithms,
medicine
has
reached
its
peak
of
interest
in
these
methods
during
the
current
pandemic.
Herein,
we
reported
several
decision
tree
algorithms
for
a
rapid
discrimination
between
coronavirus
disease
(COVID-19)
respiratory
syncytial
virus
(RSV)
infection
infants.A
cross-sectional
study
was
conducted
on
77
infants:
33
infants
with
novel
betacoronavirus
(SARS-CoV-2)
44
RSV
infection.
In
total,
23
hemogram-based
instances
were
used
to
construct
models
via
10-fold
cross-validation
method.The
Random
forest
model
showed
highest
accuracy
(81.8%),
while
terms
sensitivity
(72.7%),
specificity
(88.6%),
positive
predictive
value
(82.8%),
negative
(81.3%),
optimized
most
superior
one.Random
might
have
significant
clinical
applications,
helping
speed
up
when
SARS-CoV-2
suspected,
prior
molecular
genome
sequencing
and/or
antigen
testing.
Diagnostics,
Journal Year:
2024,
Volume and Issue:
14(13), P. 1456 - 1456
Published: July 8, 2024
The
advent
of
artificial
intelligence
(AI)
is
revolutionizing
medicine,
particularly
radiology.
With
the
development
newer
models,
AI
applications
are
demonstrating
improved
performance
and
versatile
utility
in
clinical
setting.
Thoracic
imaging
an
area
profound
interest,
given
prevalence
chest
significant
health
implications
thoracic
diseases.
This
review
aims
to
highlight
promising
within
imaging.
It
examines
role
AI,
including
its
contributions
improving
diagnostic
evaluation
interpretation,
enhancing
workflow,
aiding
invasive
procedures.
Next,
it
further
highlights
current
challenges
limitations
faced
by
such
as
necessity
'big
data',
ethical
legal
considerations,
bias
representation.
Lastly,
explores
potential
directions
for
application
