International Journal of Online and Biomedical Engineering (iJOE),
Journal Year:
2023,
Volume and Issue:
19(08), P. 144 - 162
Published: June 27, 2023
The
integration
of
Internet
Medical
Things
(IoMT)
in
Hospital
system
has
modified
the
traditional
medical
service
as
a
reactive
based
on
hospitalization
and
diseases
to
preventive
interoperable
mainly
interactive
data
flow
between
patient
health
professionals.
Using
connected
objects
(MCOs),
is
collected
processed.
According
gathered
data,
new
should
be
able
sort
states
urgent
critical
vital
signs,
consequently
priorities
are
defined.
In
this
paper,
we
direct
our
attention
manage
priority
hospital
emergencies
order
adapt
dynamically
operations
interactions
with
different
stakeholders
according
changes
their
execution
context.
Indeed,
sensed
from
MCOs
implemented
ambulances,
emergency
rooms
might
prepared
receive
injured
persons
like
victims
road
accidents
or
other
incidents.
Therefore,
design
context-aware
monitoring
framework
for
people
priorities.
In
a
nutshell,
the
IoT
refers
to
idea
of
integrating
high-tech
technology
in
form
"smart"
gadgets
and
sensors
into
single
setting
gather
data.
There
are
still
numerous
areas
which
machines
cannot
compete
favorably
with
people,
but
data
collection
analysis
undeniably
two
their
strongest
points.
The
Internet
Things
makes
it
possible
fully
or
partially
automation
data,
involves
related
activities,
is
obviously
very
important
for
healthcare
industry.
What
exactly
connected
medical
things,
how
might
make
significant
impact
on
sector?
By
having
apply
concept
internet
things
(IoT)
field
medicine,
several
advancements
have
become
possible,
including
ability
automatically
control
thermostat
containers
while
transmitting
inoculations
antibiotics,
accurate
tracking
ailments
lot
illnesses
without
need
additional
meetings
general
practitioner,
correct
most
useful
use
meds,
great
deal
more.
All
this
realizable
because
capability
MedTech
carry
out
continuous
monitoring
system.
potential
applications
interesting.
Let's
review
ways
technology.
Expert Opinion on Drug Delivery,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 8, 2024
Applying
artificial
intelligence
(AI)
to
nanomedicine
has
greatly
increased
the
production
of
specially
engineered
nanoscale
materials
for
tailored
medicine,
marking
a
significant
advancement
in
healthcare.
With
use
AI,
researchers
can
search
through
massive
databases
and
find
nano-properties
that
support
range
therapeutic
objectives,
eventually
producing
safer,
customized
nanomaterials.
AI
analyzes
patient
data,
including
clinical
genetic
information,
predict
results
individualized
care
makes
recommendations
therapy
improvement.
Furthermore,
logically
creates
nanocarriers
give
precise
controlled
drug
release
patterns
optimize
advantages
minimize
undesirable
side
effects.
Even
though
lot
potential
nanomedicine,
there
are
still
issues
data
integration
techniques,
moral
dilemmas,
requirement
governmental
backing.
Future
developments
tools
multidisciplinary
cooperation
between
scientists
with
expertise
biological
sciences
nanoengineering
essential
nanomedicine.
Together,
these
disciplines
propel
advancements
precision
contributing
ultimate
objective—a
future
which
combine
provide
really
The
authors
this
editorial
encourage
call
on
scientists,
physicians,
legislators
acknowledge
its
transform
treatment.
Chemical Society Reviews,
Journal Year:
2024,
Volume and Issue:
53(8), P. 3774 - 3828
Published: Jan. 1, 2024
Engineered
2D
nanomaterials-based
smartphone-assisted
detection
approaches
integrated
with
IoMT,
focusing
on
reliable,
sensitive,
and
rapid
diagnostics
for
COVID-19.
Clinical eHealth,
Journal Year:
2024,
Volume and Issue:
7, P. 92 - 105
Published: July 14, 2024
The
emergence
of
the
Internet
Things
(IoT)
has
sparked
a
profound
transformation
in
field
digital
health,
leading
to
rise
Medical
(IoMT).
These
IoT
applications,
while
promising
significant
enhancements
patient
care
and
health
outcomes,
simultaneously
present
myriad
ethical
dilemmas.
This
paper
aims
address
these
challenges
by
introducing
Adaptive
Ethical
Framework
for
Digital
Health
(AEFIDH),
comprehensive
evaluation
framework
designed
examine
implications
technologies
within
contexts.
AEFIDH
is
developed
using
mixed-methods
approach,
encompassing
expert
consultations,
surveys,
interviews.
approach
was
employed
validate
refine
AEFIDH,
ensuring
it
encapsulates
critical
dimensions,
including
data
privacy,
informed
consent,
user
autonomy,
algorithmic
fairness,
regulatory
compliance,
design,
equitable
access
healthcare
services.
research
reveals
pressing
issues
related
security,
autonomy
highlights
imperative
need
an
increased
focus
on
transparency
integration
considerations
design
development
applications.
Despite
certain
limitations,
provides
roadmap
guiding
responsible
development,
deployment,
utilization
its
relevance
amidst
rapidly
evolving
landscape.
contributes
novel,
dynamic
that
current
adapt
future
technological
evolutions,
thereby
fostering
resilience
face
ongoing
innovation.
framework's
inherent
adaptability
allows
evolve
tandem
with
advancements,
positioning
as
invaluable
tool
stakeholders
navigating
terrain
healthcare.
Alexandria Engineering Journal,
Journal Year:
2023,
Volume and Issue:
69, P. 571 - 583
Published: Feb. 17, 2023
Computed
Tomography
(CT)
is
one
of
the
biomedical
imaging
modalities
which
are
used
to
confirm
COVID-19
cases
and/or
identify
infected
areas
in
lung.
Therefore,
this
article
aims
at
assisting
crucial
radiological
task
by
proposing
squeeze-and-excitation
networks
(SENets)
within
Internet
medical
things
(IoMT)
framework
for
automated
segmentation
infections
lung
CT
images.
The
proposed
SE
block
has
been
directly
integrated
with
deep
residual
form
Seresnets
based
on
U-Net
and
LinkNet
models.
Extensive
tests
were
conducted
a
public
dataset
including
20
1800
+
annotated
slices
evaluate
results
our
method.
Seresnet
models
showed
good
performance
Dice
score
0.73,
structure
similarity
index
0.98,
enhanced
alignment
measure
mean
absolute
error
0.06.
This
study
demonstrated
new
advanced
tool
radiologists
achieve
automatic
using
scans.
main
prospect
research
work
deploying
IoMT
diagnosis
routine
positive
patients.
