Future Internet,
Год журнала:
2024,
Номер
16(2), С. 44 - 44
Опубликована: Янв. 28, 2024
Urban
agriculture
presents
unique
challenges,
particularly
in
the
context
of
microclimate
monitoring,
which
is
increasingly
important
food
production.
This
paper
explores
application
convolutional
neural
networks
(CNNs)
to
forecast
key
sensor
measurements
from
thermal
images
within
this
context.
research
focuses
on
using
relative
air
humidity,
soil
moisture,
and
light
intensity,
are
integral
plant
health
productivity
urban
farming
environments.
The
results
indicate
a
higher
accuracy
forecasting
humidity
moisture
levels,
with
Mean
Absolute
Percentage
Errors
(MAPEs)
range
10–12%.
These
findings
correlate
strong
dependency
these
parameters
patterns,
effectively
extracted
by
CNNs.
In
contrast,
intensity
proved
be
more
challenging,
yielding
lower
accuracy.
reduced
performance
likely
due
complex
variable
factors
that
affect
insights
gained
predictive
for
may
inform
targeted
interventions
practices,
while
highlights
need
further
into
integration
additional
data
sources
or
hybrid
modeling
approaches.
conclusion
suggests
technologies
can
significantly
enhance
maintenance
health,
leading
sustainable
efficient
practices.
However,
study
also
acknowledges
challenges
implementing
agricultural
models.
International Medical Science Research Journal,
Год журнала:
2024,
Номер
4(2), С. 126 - 140
Опубликована: Фев. 2, 2024
The
fusion
of
Artificial
Intelligence
(AI)
and
healthcare
heralds
a
new
era
innovation
transformation,
yet
it
is
not
without
its
ethical
quandaries.
This
comprehensive
review
traverses
the
intricate
landscape
where
AI
meets
healthcare,
delving
into
dilemmas
that
arise
alongside
practical
applications.
considerations
span
spectrum,
encompassing
issues
patient
privacy,
transparency,
accountability,
inadvertent
perpetuation
biases
within
algorithms.
Privacy
concerns
emerge
as
central
dilemma
providers
leverage
to
process
vast
amounts
data.
Striking
delicate
balance
between
harnessing
power
for
diagnostic
predictive
purposes
safeguarding
sensitive
medical
information
critical
challenge.
Moreover,
scrutinizes
implications
algorithms
their
potential
perpetuate
biases,
inadvertently
exacerbating
health
disparities.
A
nuanced
examination
bias
mitigation
strategies
becomes
imperative
ensure
technologies
contribute
equitable
outcomes.
In
tandem
with
considerations,
illuminates
applications
reshaping
landscape.
AI-driven
diagnostics,
modeling,
personalized
treatment
plans
transformative
tools,
enhancing
clinical
decision-making
efficient
allocation
resources,
streamlined
workflows,
acceleration
drug
discovery
processes
showcase
tangible
benefits
integration.
aspires
guide
practitioners,
policymakers,
technologists
in
navigating
crossroads
healthcare.
By
fostering
an
awareness
pitfalls
emphasizing
responsible
development,
stakeholders
can
collaboratively
shape
future
augments
delivery,
upholds
standards,
ultimately
improves
quality
care.
Keywords:
AI,
Healthcare,
Ethics,
Review,
Application.
Journal of Medical Systems,
Год журнала:
2025,
Номер
49(1)
Опубликована: Янв. 16, 2025
Generative
Artificial
Intelligence
(Gen
AI)
has
transformative
potential
in
healthcare
to
enhance
patient
care,
personalize
treatment
options,
train
professionals,
and
advance
medical
research.
This
paper
examines
various
clinical
non-clinical
applications
of
Gen
AI.
In
settings,
AI
supports
the
creation
customized
plans,
generation
synthetic
data,
analysis
images,
nursing
workflow
management,
risk
prediction,
pandemic
preparedness,
population
health
management.
By
automating
administrative
tasks
such
as
documentations,
reduce
clinician
burnout,
freeing
more
time
for
direct
care.
Furthermore,
application
may
surgical
outcomes
by
providing
real-time
feedback
automation
certain
operating
rooms.
The
data
opens
new
avenues
model
training
diseases
simulation,
enhancing
research
capabilities
improving
predictive
accuracy.
contexts,
improves
education,
public
relations,
revenue
cycle
marketing
etc.
Its
capacity
continuous
learning
adaptation
enables
it
drive
ongoing
improvements
operational
efficiencies,
making
delivery
proactive,
predictive,
precise.
World Journal of Advanced Research and Reviews,
Год журнала:
2023,
Номер
20(3), С. 1293 - 1302
Опубликована: Дек. 22, 2023
This
research
explores
the
confluence
of
big
data
analytics
and
Geographic
information
systems
(GIS)
in
healthcare
decision-making.
The
comparative
review
delineates
unique
strengths
each
technology,
showcasing
potential
synergies.
Big
harnesses
advanced
for
predictive
modeling
clinical
decision
support,
while
GIS
introduces
a
spatial
context
health
analysis.
Future
trends
suggest
integrations
with
artificial
intelligence,
real-time
analytics,
wearable
technology.
However,
challenges
encompass
privacy,
biases,
interdisciplinary
collaboration.
Ethical
considerations
emphasize
transparency,
informed
consent,
responsible
use
patient
data.
As
these
technologies
evolve,
their
seamless
integration
holds
promise
precision
health,
community-oriented
interventions,
proactive
pandemic
response,
reshaping
landscape
Applied Sciences,
Год журнала:
2024,
Номер
14(22), С. 10144 - 10144
Опубликована: Ноя. 6, 2024
The
integration
of
artificial
intelligence
(AI)
in
healthcare
management
marks
a
significant
advance
technological
innovation,
promising
transformative
effects
on
processes,
patient
care,
and
the
efficacy
emergency
responses.
scientific
novelty
study
lies
its
integrated
approach,
combining
systematic
review
predictive
algorithms
to
provide
comprehensive
understanding
AI’s
role
improving
across
different
contexts.
Covering
period
between
2019
2023,
which
includes
global
challenges
posed
by
COVID-19
pandemic,
this
research
investigates
operational,
strategic,
response
implications
AI
adoption
sector.
It
further
examines
how
impact
varies
temporal
geographical
addresses
two
main
objectives:
explore
influences
domains,
identify
variations
based
Utilizing
an
we
compared
various
prediction
algorithms,
including
logistic
regression,
interpreted
results
through
SHAP
(SHapley
Additive
exPlanations)
analysis.
findings
reveal
five
key
thematic
areas:
enhancing
quality
assurance,
resource
management,
security,
pandemic.
highlights
positive
influence
operational
efficiency
strategic
decision
making,
while
also
identifying
related
data
privacy,
ethical
considerations,
need
for
ongoing
integration.
These
insights
opportunities
targeted
interventions
optimize
current
future
landscapes.
In
conclusion,
work
contributes
deeper
provides
policymakers,
professionals,
researchers,
offering
roadmap
addressing
both
Diagnostics,
Год журнала:
2024,
Номер
14(4), С. 397 - 397
Опубликована: Фев. 12, 2024
Artificial
intelligence
(AI)
has
emerged
as
a
promising
tool
in
the
field
of
healthcare,
with
an
increasing
number
research
articles
evaluating
its
applications
domain
kidney
disease.
To
comprehend
evolving
landscape
AI
disease,
bibliometric
analysis
is
essential.
The
purposes
this
study
are
to
systematically
analyze
and
quantify
scientific
output,
trends,
collaborative
networks
application
This
collected
AI-related
published
between
2012
20
November
2023
from
Web
Science.
Descriptive
analyses
trends
disease
were
used
determine
growth
rate
publications
by
authors,
journals,
institutions,
countries.
Visualization
network
maps
country
collaborations
author-provided
keyword
co-occurrences
generated
show
hotspots
on
initial
search
yielded
673
articles,
which
631
included
analyses.
Our
findings
reveal
noteworthy
exponential
trend
annual
Medicine,
Год журнала:
2024,
Номер
103(28), С. e38834 - e38834
Опубликована: Июль 12, 2024
Epidemic
outbreaks
of
infectious
diseases
in
conflict
zones
are
complex
threats
to
public
health
and
humanitarian
activities
that
require
creativity
approaches
reducing
their
damage.
This
narrative
review
focuses
on
the
technology
intersection
with
disease
response
zones,
complexity
healthcare
infrastructure,
population
displacement,
security
risks.
explores
how
conflict-related
destruction
is
harmful
towards
systems
impediments
surveillance
activities.
In
this
regards,
also
considered
contributions
technological
innovations,
such
as
improvement
epidemiological
surveillance,
mobile
(mHealth)
technologies,
genomic
sequencing,
strengthening
management
settings.
Ethical
issues
related
data
privacy,
fairness
covered.
By
advisement
policy
investment
systems,
diagnostic
capacity,
capacity
building,
collaboration,
even
ethical
governance,
stakeholders
can
leverage
enhance
settings
and,
thus,
protect
global
security.
full
information
for
researchers,
policymakers,
practitioners
who
dealing
conflicts
worn
areas.
BioMedInformatics,
Год журнала:
2024,
Номер
4(1), С. 673 - 689
Опубликована: Март 1, 2024
This
review
explores
the
integration
of
artificial
intelligence
(AI)
and
machine
learning
(ML)
into
kidney
transplantation
(KT),
set
against
backdrop
a
significant
donor
organ
shortage
evolution
‘Next-Generation
Healthcare’.
Its
purpose
is
to
evaluate
how
AI
ML
can
enhance
process,
from
selection
postoperative
patient
care.
Our
methodology
involved
comprehensive
current
research,
focusing
on
application
in
various
stages
KT.
included
an
analysis
donor–recipient
matching,
predictive
modeling,
improvement
The
results
indicated
that
significantly
improve
efficiency
success
rates
They
aid
better
reduce
rejection,
monitoring
Predictive
based
extensive
data
analysis,
has
been
particularly
effective
identifying
suitable
matches
anticipating
complications.
In
conclusion,
this
discusses
transformative
impact
KT,
offering
more
precise,
personalized,
healthcare
solutions.
Their
field
addresses
critical
issues
like
shortages
post-transplant
However,
successful
these
technologies
requires
careful
consideration
their
ethical,
privacy,
training
aspects
settings.
Healthcare,
Год журнала:
2024,
Номер
12(24), С. 2587 - 2587
Опубликована: Дек. 22, 2024
Federated
learning
(FL)
is
revolutionizing
healthcare
by
enabling
collaborative
machine
across
institutions
while
preserving
patient
privacy
and
meeting
regulatory
standards.
This
review
delves
into
FL's
applications
within
smart
health
systems,
particularly
its
integration
with
IoT
devices,
wearables,
remote
monitoring,
which
empower
real-time,
decentralized
data
processing
for
predictive
analytics
personalized
care.
It
addresses
key
challenges,
including
security
risks
like
adversarial
attacks,
poisoning,
model
inversion.
Additionally,
it
covers
issues
related
to
heterogeneity,
scalability,
system
interoperability.
Alongside
these,
the
highlights
emerging
privacy-preserving
solutions,
such
as
differential
secure
multiparty
computation,
critical
overcoming
limitations.
Successfully
addressing
these
hurdles
essential
enhancing
efficiency,
accuracy,
broader
adoption
in
healthcare.
Ultimately,
FL
offers
transformative
potential
secure,
data-driven
promising
improved
outcomes,
operational
sovereignty
ecosystem.
Micromachines,
Год журнала:
2024,
Номер
15(8), С. 1059 - 1059
Опубликована: Авг. 22, 2024
A
novel,
portable
deep
learning-assisted
smartphone-based
electrochemiluminescence
(ECL)
cost-effective
(~10$)
sensing
platform
was
developed
and
used
for
selective
detection
of
lactate.
Low-cost,
fast
prototyping
screen
printing
wax
methods
with
paper-based
substrate
were
to
fabricate
miniaturized
single-pair
electrode
ECL
platforms.
The
lab-made
3D-printed
black
box
served
as
a
reaction
chamber.
This
integrated
smartphone
buck-boost
converter,
eliminating
the
need
expensive
CCD
cameras,
photomultiplier
tubes,
bulky
power
supplies.
advancement
makes
this
ideal
point-of-care
testing
applications.
Foremost,
integration
learning
approach
enhance
not
just
accuracy
sensors,
but
also
expedite
diagnostic
procedure.
models
trained
(3600
images)
tested
(900
using
images
obtained
from
experimentation.
Herein,
user
convenience,
an
Android
application
graphical
interface
developed.
app
performs
several
tasks,
which
include
capturing
real-time
images,
cropping
them,
predicting
concentration
required
bioanalytes
through
learning.
device’s
capability
work
in
real
environment
by
performing
lactate
sensing.
fabricated
device
shows
good
liner
range
(from
50
µM
2000
µM)
acceptable
limit
value
5.14
µM.
Finally,
various
rigorous
analyses,
including
stability,
reproducibility,
unknown
sample
analysis,
conducted
check
durability
stability.
Therefore,
becomes
versatile
applicable
across
domains
harnessing
cutting-edge
technology
integrating
it
smartphone.