Telematics and Informatics Reports,
Год журнала:
2023,
Номер
11, С. 100097 - 100097
Опубликована: Сен. 1, 2023
Deep
learning
and
machine
techniques
present
unmatched
opportunities
to
improve
healthcare
in
sub-Saharan
Africa
(SSA).
However,
there
is
a
paucity
of
literature
on
AI-based
applications
deployed
care
SSA,
which
makes
it
challenging
organise
the
research
contributions
highlight
obstacles
emerging
areas
that
need
be
explored
future.
This
study
applied
PRISMA
(Preferred
Reporting
Items
for
Systematic
Reviews
Meta-Analysis)
model
conduct
comprehensive
review
deep
models
SSA
access
while
exploring
opportunities,
trends
implications
integrating
healthcare.
reveals
AI
can
analyse
derive
inferences
from
massive
health
data
early
detection,
diagnosis,
monitoring
chronic
disorders,
prediction
diseases,
large-scale
public
patterns
help
limit
exposure
contagious
environments.
facilitate
development
targeted
interventions
patient
outcomes
all
stages
treatment,
drug
monitoring,
personalised
medicine,
control
care.
Integrating
with
tremendously
assist
professionals
policymakers
disease
diagnosis
making
informed
decisions.
algorithms
bias,
poor
formats,
lack
policies
frameworks
supporting
integration
data-driven
solutions
into
systems
hinder
systems.
There
transparency
ethical
use
crafting
support
Utilising
also
researchers
workers
move
towards
smart
better
comprehend
future
needs
IEEE Access,
Год журнала:
2022,
Номер
10, С. 90792 - 90826
Опубликована: Янв. 1, 2022
The
smart
healthcare
system
has
improved
the
patients
quality
of
life
(QoL),
where
records
are
being
analyzed
remotely
by
distributed
stakeholders.
It
requires
a
voluminous
exchange
data
for
disease
prediction
via
open
communication
channel,
i.e.,
Internet
to
train
artificial
intelligence
(AI)
models
efficiently
and
effectively.
nature
channels
puts
privacy
at
high
risk
affects
model
training
collected
centralized
servers.
To
overcome
this,
an
emerging
concept,
federated
learning
(FL)
is
viable
solution.
performs
client
nodes
aggregates
their
results
global
model.
concept
local
preserves
privacy,
confidentiality,
integrity
patient's
which
contributes
effectively
process.
applicability
FL
in
domain
various
advantages,
but
it
not
been
explored
its
extent.
existing
surveys
majorly
focused
on
role
diverse
applications,
there
exists
no
detailed
or
comprehensive
survey
informatics
(HI).
We
present
relative
comparison
recent
with
proposed
survey.
strengthen
increase
QoL
patients,
we
FL-based
layered
architecture
along
case
study
electronic
health
(FL-EHR).
discuss
models,
statistical
security
challenges
adoption
medical
setups.
Thus,
review
presents
useful
insights
both
academia
practitioners
investigate
application
HI
ecosystems.
Sensors International,
Год журнала:
2022,
Номер
3, С. 100156 - 100156
Опубликована: Янв. 1, 2022
The
adoption
of
non-invasive
smart
implants
is
inevitable
due
to
recent
technological
advancements
in
and
the
increasing
demand
provide
pervasive
personalized
care.
integration
presents
unprecedented
opportunities
for
effective
disease
prevention,
real-time
health
data
collection,
early
detection
diseases,
monitoring
chronic
virtual
patient
care,
patient-tailored
treatment,
minimally
invasive
management
diseases.
Even
though
research
work
this
area
nascent,
study
potential
benefits
use
healthcare
while
reflecting
on
challenges
limitations
their
utilization.
With
current
advancements,
regaining
momentum
managing
conditions
diseases
such
as
cancer,
cardiovascular
cognitive
impairment;
orthopedic
surgery,
dental
surgery;
remotely
infectious
novel
coronavirus
2019
(COVID-19).
However,
full
utilization
still
encounter
barriers
lack
policies
frameworks
regulating
use,
limited
memory
space,
consequences
implants'
failure,
clinical
challenges,
hazards
imposed
by
implants,
security,
privacy
risks.
Therefore,
there
a
need
robust
security
measures
well
formulation
guiding
development
implants.
gained
experience
from
next
generation
may
include
sophisticated
modern
computational
techniques
that
can
analyze
suggest
adequate
therapeutic
actions.
IEEE Transactions on Neural Systems and Rehabilitation Engineering,
Год журнала:
2023,
Номер
31, С. 2399 - 2423
Опубликована: Янв. 1, 2023
Parkinson's
Disease
(PD)
is
among
the
most
frequent
neurological
disorders.
Approaches
that
employ
artificial
intelligence
and
notably
deep
learning,
have
been
extensively
embraced
with
promising
outcomes.
This
study
dispenses
an
exhaustive
review
between
2016
January
2023
on
learning
techniques
used
in
prognosis
evolution
of
symptoms
characteristics
disease
based
gait,
upper
limb
movement,
speech
facial
expression-related
information
as
well
fusion
more
than
one
aforementioned
modalities.
The
search
resulted
selection
87
original
research
publications,
which
we
summarized
relevant
regarding
utilized
development
process,
demographic
information,
primary
outcomes,
sensory
equipment
related
information.
Various
algorithms
frameworks
attained
state-of-the-art
performance
many
PD-related
tasks
by
outperforming
conventional
machine
approaches,
according
to
reviewed.
In
meanwhile,
identify
significant
drawbacks
existing
research,
including
a
lack
data
availability
interpretability
models.
fast
advancements
rise
accessible
provide
opportunity
address
these
difficulties
near
future
for
broad
application
this
technology
clinical
settings.
World Journal of Advanced Research and Reviews,
Год журнала:
2023,
Номер
21(2), С. 432 - 440
Опубликована: Фев. 28, 2023
This
paper
reviews
the
effectiveness
of
health
apps
and
their
impact
on
patient
engagement,
focusing
role
user
experience
(UX)
in
enhancing
engagement
healthcare
outcomes.
A
comprehensive
literature
analysis
categorizes
types
evaluates
improving
Key
UX
principles
essential
for
app
design
are
outlined,
influence
is
analyzed.
The
review
identifies
technological
ethical
challenges
development,
including
privacy
concerns
need
inclusive
design.
Future
research
directions
suggested,
highlighting
areas
further
exploration
engagement.
findings
emphasize
importance
effective
superior
fostering
with
implications
providers,
patients,
developers
leveraging
digital
technologies
to
enhance
delivery
well-being.
Telematics and Informatics Reports,
Год журнала:
2023,
Номер
11, С. 100097 - 100097
Опубликована: Сен. 1, 2023
Deep
learning
and
machine
techniques
present
unmatched
opportunities
to
improve
healthcare
in
sub-Saharan
Africa
(SSA).
However,
there
is
a
paucity
of
literature
on
AI-based
applications
deployed
care
SSA,
which
makes
it
challenging
organise
the
research
contributions
highlight
obstacles
emerging
areas
that
need
be
explored
future.
This
study
applied
PRISMA
(Preferred
Reporting
Items
for
Systematic
Reviews
Meta-Analysis)
model
conduct
comprehensive
review
deep
models
SSA
access
while
exploring
opportunities,
trends
implications
integrating
healthcare.
reveals
AI
can
analyse
derive
inferences
from
massive
health
data
early
detection,
diagnosis,
monitoring
chronic
disorders,
prediction
diseases,
large-scale
public
patterns
help
limit
exposure
contagious
environments.
facilitate
development
targeted
interventions
patient
outcomes
all
stages
treatment,
drug
monitoring,
personalised
medicine,
control
care.
Integrating
with
tremendously
assist
professionals
policymakers
disease
diagnosis
making
informed
decisions.
algorithms
bias,
poor
formats,
lack
policies
frameworks
supporting
integration
data-driven
solutions
into
systems
hinder
systems.
There
transparency
ethical
use
crafting
support
Utilising
also
researchers
workers
move
towards
smart
better
comprehend
future
needs
