Advances in healthcare information systems and administration book series,
Год журнала:
2024,
Номер
unknown, С. 348 - 370
Опубликована: Май 17, 2024
The
healthcare
industry
is
transforming
significantly
due
to
the
rapid
emergence
of
internet
medical
things
(IoMT).
integration
cutting-edge
technologies
facilitates
this
paradigm
shift.
A
new
age
system
optimization
and
patient
care
being
ushered
in.
This
study
provides
a
comprehensive
overview
future
trends
open
issues
in
adopting
IoMTs.
It
explores
current
status
IoMT
forecasts
its
evolution.
examines
policy
regulatory
ramifications
essential
ethical
data
privacy
aspects.
More
still
elucidates
urgent
security,
interoperability,
scalability
difficulties
while
underscoring
imperative
for
collaborative
efforts
standards
within
industry.
affords
insights
research
by
presenting
set
unanswered
inquiries
corresponding
possible
implications,
accompanied
relevant
cases.
Finally,
it
emphasizes
significant
impact
can
have
on
availing
lightweight
digital
trust
architectures.
Computers in Biology and Medicine,
Год журнала:
2024,
Номер
170, С. 108036 - 108036
Опубликована: Янв. 28, 2024
Over
the
past
five
years,
interest
in
literature
regarding
security
of
Internet
Medical
Things
(IoMT)
has
increased.
Due
to
enhanced
interconnectedness
IoMT
devices,
their
susceptibility
cyber-attacks
proportionally
escalated.
Motivated
by
promising
potential
AI-related
technologies
improve
certain
cybersecurity
measures,
we
present
a
comprehensive
review
this
emerging
field.
In
review,
attempt
bridge
corresponding
gap
modern
that
deploy
AI
techniques
performance
and
compensate
for
privacy
vulnerabilities.
direction,
have
systematically
gathered
classified
extensive
research
on
topic.
Our
findings
highlight
fact
integration
machine
learning
(ML)
deep
(DL)
improves
both
measures
speed,
reliability,
effectiveness.
This
may
be
proven
useful
improving
devices.
Furthermore,
considering
numerous
advantages
as
opposed
core
counterparts,
including
blockchain,
anomaly
detection,
homomorphic
encryption,
differential
privacy,
federated
learning,
so
on,
provide
structured
overview
current
scientific
trends.
We
conclude
with
considerations
future
research,
emphasizing
AI-driven
landscape,
especially
patient
data
protection
data-driven
healthcare.
IEEE Communications Surveys & Tutorials,
Год журнала:
2024,
Номер
26(3), С. 1861 - 1897
Опубликована: Янв. 1, 2024
Due
to
the
greatly
improved
capabilities
of
devices,
massive
data,
and
increasing
concern
about
data
privacy,
Federated
Learning
(FL)
has
been
increasingly
considered
for
applications
wireless
communication
networks
(WCNs).
Wireless
FL
(WFL)
is
a
distributed
method
training
global
deep
learning
model
in
which
large
number
participants
each
train
local
on
their
datasets
then
upload
updates
central
server.
However,
general,
nonindependent
identically
(non-IID)
WCNs
raises
concerns
robustness,
as
malicious
participant
could
potentially
inject
"backdoor"
into
by
uploading
poisoned
or
models
over
WCN.
This
cause
misclassify
inputs
specific
target
class
while
behaving
normally
with
benign
inputs.
survey
provides
comprehensive
review
latest
backdoor
attacks
defense
mechanisms.
It
classifies
them
according
targets
(data
poisoning
poisoning),
attack
phase
(local
collection,
training,
aggregation),
stage
before
aggregation,
during
after
aggregation).
The
strengths
limitations
existing
strategies
mechanisms
are
analyzed
detail.
Comparisons
methods
designs
carried
out,
pointing
noteworthy
findings,
open
challenges,
potential
future
research
directions
related
security
privacy
WFL.
Future Internet,
Год журнала:
2024,
Номер
16(9), С. 329 - 329
Опубликована: Сен. 10, 2024
Edge
computing
promising
a
vision
of
processing
data
close
to
its
generation
point,
reducing
latency
and
bandwidth
usage
compared
with
traditional
cloud
architectures,
has
attracted
significant
attention
lately.
The
integration
edge
in
modern
systems
takes
advantage
Internet
Things
(IoT)
devices
can
potentially
improve
the
systems’
performance,
scalability,
privacy,
security
applications
different
domains.
In
healthcare
domain,
IoT
nowadays
be
used
gather
vital
parameters
information
that
fed
Artificial
Intelligence
(AI)
techniques
able
offer
precious
insights
support
professionals.
However,
issues
regarding
privacy
security,
AI
optimization,
computational
offloading
at
pose
challenges
adoption
AI.
This
paper
aims
explore
current
state
art
by
using
Preferred
Reporting
Items
for
Systematic
Reviews
Meta-Analyses
(PRISMA)
methodology
analyzing
more
than
70
Web
Science
articles.
We
have
defined
relevant
research
questions,
clear
inclusion
exclusion
criteria,
classified
works
three
main
directions:
AI-based
optimization
methods,
techniques.
findings
highlight
many
advantages
integrating
wide
range
use
cases
requiring
near
real-time
decision-making,
efficient
communication
links,
potential
transform
future
services
eHealth
applications.
further
is
needed
enforce
new
security-preserving
methods
better
orchestrating
coordinating
load
distributed
decentralized
scenarios.
Advances in medical diagnosis, treatment, and care (AMDTC) book series,
Год журнала:
2024,
Номер
unknown, С. 304 - 323
Опубликована: Янв. 5, 2024
The
healthcare
industry
is
undergoing
a
momentous
transformation
with
the
advent
of
artificial
intelligence
(AI)
and
internet
medical
things
(IoMT),
as
these
technologies
are
significant
in
managing
patient
data,
simple
surgery,
personnel.
This
development
has
shown
potential
to
mitigate
shortages,
health
issues,
global
disasters.
Nevertheless,
dynamic
characteristics
system
its
vulnerability
intrusions
give
rise
apprehensions
regarding
possible
compromise
endangerment
life,
reputational
harm.
study
examines
influence
robots
AI-aided
diagnostics
on
smart
sustainability.
Advances in computational intelligence and robotics book series,
Год журнала:
2024,
Номер
unknown, С. 308 - 333
Опубликована: Апрель 1, 2024
This
study
examines
the
complex
array
of
impediments
and
potential
advantages
internet
things
(IoT)-enabled
secure
intelligent
smart
healthcare
devices
(IESISHDs)
associated
with
shift
towards
enabling
cities,
motivated
by
pressing
necessity
to
address
climate
change
promote
sustaining
systems.
looks
at
technological,
economic,
social
problems
that
need
be
solved
in
order
make
cities
smarter
IoT.
It
does
this
reading
a
lot
scholarly
sources.
Most
stupendously,
it
emphasizes
environmentally
sustainable
merits,
for
economic
growth,
improvements
societal
well-being
can
arise
from
transition.
further
depicts
selected
case
studies
demonstrate
empirical
evidence
provide
policy
recommendations.
The
paradigm
is
assist
governments
other
stakeholders
effectively
managing
human-associated
challenges
attain
maximum
value
an
innovative
future
guarantees
worldwide
prosperity
ecological
welfare.
Artificial Intelligence Review,
Год журнала:
2025,
Номер
58(3)
Опубликована: Янв. 8, 2025
Abstract
This
paper
explores
the
transformative
impact
of
Internet
Medical
Things
(IoMT)
on
healthcare.
By
integrating
medical
equipment
and
sensors
with
internet,
IoMT
enables
real-time
monitoring
patient
health,
remote
care,
individualized
treatment
plans.
significantly
improves
several
healthcare
domains,
including
managing
chronic
diseases,
safety,
drug
adherence,
resulting
in
better
outcomes
reduced
expenses.
Technologies
like
blockchain,
Artificial
Intelligence
(AI),
cloud
computing
further
boost
IoMT’s
capabilities
Blockchain
enhances
data
security
interoperability,
AI
analyzes
massive
volumes
health
to
find
patterns
make
predictions,
offers
scalable
cost-effective
processing
storage.
Therefore,
this
provides
a
comprehensive
review
(IoT)
IoMT-based
edge-intelligent
smart
healthcare,
focusing
publications
published
between
2018
2024.
The
addresses
numerous
studies
IoT,
IoMT,
AI,
edge
computing,
security,
Deep
Learning,
blockchain.
obstacles
facing
are
also
covered
paper,
interoperability
issues,
regulatory
compliance,
privacy
concerns.
Finally,
recommendations
for
provided.
