Future Internet,
Год журнала:
2024,
Номер
16(9), С. 308 - 308
Опубликована: Авг. 27, 2024
The
rapid
development
of
AI
technology
in
recent
years
has
led
to
its
widespread
use
daily
life,
where
it
plays
an
increasingly
important
role.
In
healthcare,
been
integrated
into
the
field
develop
new
domain
smart
healthcare.
opportunities
and
challenges
coexist.
This
article
provides
a
comprehensive
overview
past
developments
progress
this
area.
First,
we
summarize
definition
characteristics
Second,
explore
that
brings
healthcare
from
macro
perspective.
Third,
categorize
specific
applications
ten
domains
discuss
their
technological
foundations
individually.
Finally,
identify
key
these
face
existing
solutions
for
each.
Journal of Medicine Surgery and Public Health,
Год журнала:
2024,
Номер
3, С. 100099 - 100099
Опубликована: Апрель 17, 2024
Artificial
Intelligence
(AI)
has
emerged
as
a
transformative
force
in
various
fields,
and
its
application
mental
healthcare
is
no
exception.
Hence,
this
review
explores
the
integration
of
AI
into
healthcare,
elucidating
current
trends,
ethical
considerations,
future
directions
dynamic
field.
This
encompassed
recent
studies,
examples
applications,
considerations
shaping
Additionally,
regulatory
frameworks
trends
research
development
were
analyzed.
We
comprehensively
searched
four
databases
(PubMed,
IEEE
Xplore,
PsycINFO,
Google
Scholar).
The
inclusion
criteria
papers
published
peer-reviewed
journals,
conference
proceedings,
or
reputable
online
databases,
that
specifically
focus
on
field
offer
comprehensive
overview,
analysis,
existing
literature
English
language.
Current
reveal
AI's
potential,
with
applications
such
early
detection
health
disorders,
personalized
treatment
plans,
AI-driven
virtual
therapists.
However,
these
advancements
are
accompanied
by
challenges
concerning
privacy,
bias
mitigation,
preservation
human
element
therapy.
Future
emphasize
need
for
clear
frameworks,
transparent
validation
models,
continuous
efforts.
Integrating
therapy
represents
promising
frontier
healthcare.
While
holds
potential
to
revolutionize
responsible
implementation
essential.
By
addressing
thoughtfully,
we
may
effectively
utilize
enhance
accessibility,
efficacy,
ethicality
thereby
helping
both
individuals
communities.
Waste Management Bulletin,
Год журнала:
2024,
Номер
2(2), С. 244 - 263
Опубликована: Май 9, 2024
Waste
management
poses
a
pressing
global
challenge,
necessitating
innovative
solutions
for
resource
optimization
and
sustainability.
Traditional
practices
often
prove
insufficient
in
addressing
the
escalating
volume
of
waste
its
environmental
impact.
However,
advent
Artificial
Intelligence
(AI)
technologies
offers
promising
avenues
tackling
complexities
systems.
This
review
provides
comprehensive
examination
AI's
role
management,
encompassing
collection,
sorting,
recycling,
monitoring.
It
delineates
potential
benefits
challenges
associated
with
each
application
while
emphasizing
imperative
improved
data
quality,
privacy
measures,
cost-effectiveness,
ethical
considerations.
Furthermore,
future
prospects
AI
integration
Internet
Things
(IoT),
advancements
machine
learning,
importance
collaborative
frameworks
policy
initiatives
were
discussed.
In
conclusion,
holds
significant
promise
enhancing
practices,
such
as
concerns,
cost
implications
is
paramount.
Through
concerted
efforts
ongoing
research
endeavors,
transformative
can
be
fully
harnessed
to
drive
sustainable
efficient
practices.
Journal of Medicine Surgery and Public Health,
Год журнала:
2024,
Номер
3, С. 100108 - 100108
Опубликована: Апрель 16, 2024
This
review
provides
a
comprehensive
examination
of
the
integration
Artificial
Intelligence
(AI)
into
healthcare,
focusing
on
its
transformative
implications
and
challenges.
Utilising
systematic
search
strategy
across
electronic
databases
such
as
PubMed,
Scopus,
Embase,
Sciencedirect,
relevant
peer-reviewed
articles
published
in
English
between
January
2010
till
date
were
identified.
Findings
reveal
AI's
significant
impact
healthcare
delivery,
including
role
enhancing
diagnostic
precision,
enabling
treatment
personalisation,
facilitating
predictive
analytics,
automating
tasks,
driving
robotics.
AI
algorithms
demonstrate
high
accuracy
analysing
medical
images
for
disease
diagnosis
enable
creation
tailored
plans
based
patient
data
analysis.
Predictive
analytics
identify
high-risk
patients
proactive
interventions,
while
AI-powered
tools
streamline
workflows,
improving
efficiency
experience.
Additionally,
AI-driven
robotics
automate
tasks
enhance
care
particularly
rehabilitation
surgery.
However,
challenges
quality,
interpretability,
bias,
regulatory
frameworks
must
be
addressed
responsible
implementation.
Recommendations
emphasise
need
robust
ethical
legal
frameworks,
human-AI
collaboration,
safety
validation,
education,
regulation
to
ensure
effective
healthcare.
valuable
insights
potential
advocating
implementation
efficacy.
Journal of Microbiological Methods,
Год журнала:
2024,
Номер
224, С. 106998 - 106998
Опубликована: Июль 15, 2024
Vaccine
development
stands
as
a
cornerstone
of
public
health
efforts,
pivotal
in
curbing
infectious
diseases
and
reducing
global
morbidity
mortality.
However,
traditional
vaccine
methods
are
often
time-consuming,
costly,
inefficient.
The
advent
artificial
intelligence
(AI)
has
ushered
new
era
design,
offering
unprecedented
opportunities
to
expedite
the
process.
This
narrative
review
explores
role
AI
development,
focusing
on
antigen
selection,
epitope
prediction,
adjuvant
identification,
optimization
strategies.
algorithms,
including
machine
learning
deep
learning,
leverage
genomic
data,
protein
structures,
immune
system
interactions
predict
antigenic
epitopes,
assess
immunogenicity,
prioritize
antigens
for
experimentation.
Furthermore,
AI-driven
approaches
facilitate
rational
design
immunogens
identification
novel
candidates
with
optimal
safety
efficacy
profiles.
Challenges
such
data
heterogeneity,
model
interpretability,
regulatory
considerations
must
be
addressed
realize
full
potential
development.
Integrating
emerging
technologies,
single-cell
omics
synthetic
biology,
promises
enhance
precision
scalability.
underscores
transformative
impact
highlights
need
interdisciplinary
collaborations
harmonization
accelerate
delivery
safe
effective
vaccines
against
diseases.
Journal of Medicine Surgery and Public Health,
Год журнала:
2024,
Номер
3, С. 100109 - 100109
Опубликована: Апрель 23, 2024
Using
Artificial
intelligence
technologies
in
cardiology
has
witnessed
rapid
advancements
across
various
domains,
fostering
innovation
and
reshaping
clinical
practices.
The
study
aims
to
provide
a
comprehensive
overview
of
these
AI-driven
their
implications
for
enhancing
cardiovascular
healthcare.
A
systematic
approach
was
adopted
conduct
an
extensive
review
scholarly
articles
peer-reviewed
literature
focusing
on
the
application
AI
cardiology.
Databases
including
PubMed/MEDLINE,
ScienceDirect,
IEEE
Xplore,
Web
Science
were
systematically
searched.
Articles
screened
following
defined
selection
criteria.
These
articles'
synthesis
highlighted
AI's
diverse
applications
cardiology,
but
not
limited
diagnostic
innovations,
precision
medicine,
remote
monitoring
technologies,
drug
discovery,
decision
support
systems.
shows
significant
role
medicine
by
revolutionising
diagnostics,
treatment
strategies,
patient
care.
showcased
this
reflect
transformative
potential
technologies.
However,
challenges
such
as
algorithm
accuracy,
interoperability,
integration
into
workflows
persist.
continued
strategic
promise
deliver
more
personalised,
efficient,
effective
care,
ultimately
improving
outcomes
shaping
future
practice.
Clinica Chimica Acta,
Год журнала:
2025,
Номер
569, С. 120181 - 120181
Опубликована: Фев. 3, 2025
The
integration
of
artificial
intelligence
(AI)
into
laboratory
medicine,
is
revolutionizing
diagnostic
accuracy,
operational
efficiency,
and
personalized
patient
care.
AI
technologies(machine
learning,
natural
language
processing
computer
vision)
advance
evidence-based
medicine
(EBLM)
by
automating
optimizing
critical
processes(formulating
clinical
questions,
conducting
literature
searches,
appraising
evidence,
developing
guidelines).
These
reduce
the
time
for
systematic
reviews,
ensuring
consistency
in
appraisal,
enabling
real-time
updates
to
guidelines.
supports
analyzing
large
datasets,
genetic
information
electronic
health
records
(EHRs),
tailor
treatment
plans
profiles.
Predictive
analytics
enhance
outcomes
leveraging
historical
data
ongoing
monitoring
predict
responses
optimize
care
pathways.
Despite
transformative
potential,
there
are
challenges.
transparency,
explainability
algorithms
gaining
trust
ethical
deployment.
Integration
existing
workflows
requires
collaboration
between
developers
users
ensure
seamless
user-friendly
adoption.
Ethical
considerations,
such
as
privacy,data
security,
algorithmic
bias,
must
also
be
addressed
mitigate
risks
equitable
healthcare
delivery.
Regulatory
frameworks,
eg.
EU
Regulation,
emphasize
governance,
human
oversight,
particularly
high-risk
systems.
economic
benefits
cost
savings,
improved
precision,
enhanced
outcomes.
Future
trends
(federated
learning
self-supervised
learning),
will
scalability
applicability
EBLM,
paving
way
a
new
era
precision
medicine.
EBLM
has
potential
transform
delivery,
improve
outcomes,
personalized/precision
Advances in healthcare information systems and administration book series,
Год журнала:
2024,
Номер
unknown, С. 261 - 282
Опубликована: Фев. 9, 2024
Recent
years
have
witnessed
a
significant
convergence
of
artificial
intelligence
(AI)
within
the
healthcare
sector.
This
chapter
explores
transformative
potential
and
challenges
posed
by
these
intelligent
technologies
in
healthcare.
It
various
domains
such
as
predictive
analytics,
telemedicine,
personalized
medicine,
enhancement
operational
efficiencies.
The
findings
underscore
AI
smart
revolutionizing
delivery.
carries
extensive
implications
for
Healthcare
practitioners
administrators
can
leverage
insights
to
strategically
incorporate
solutions,
aiming
improve
patient
outcomes
enhance
organizational
efficiency.
Additionally,
provide
valuable
guidance
policymakers
stakeholders,
informing
creation
guidelines
standards
that
foster
innovation,
ensure
safety,
protect
data
security.
Therefore,
this
is
an
essential
guide
effectively
embracing
role
advancing
practices.
Journal of Public Health,
Год журнала:
2024,
Номер
46(2), С. 207 - 208
Опубликована: Апрель 11, 2024
What's
artificial
intelligence
(AI)
got
to
do
with
it-inequality
and
public
health?'We
must
work
together
for
AI
that
bridges
social,
digital,
economic
divides,
not
one
pushes
us
further
apart.'
1In
his
article
'Getting
Right'
2
James
Maniyka
writes:
'While
the
headlines
tend
feature
results
demonstrations
of
a
future
come,
its
associated
technologies
are
already
here
pervade
our
daily
lives
more
than
many
realize.Examples
include
recommendation
systems,
search,
language
translators-now
covering
hundred
languages-facial
recognition,
speech
text
(and
back),
digital
assistants,
chatbots
customer
service,
fraud
detection,
decision
support
energy
management
tools
scientific
research,
name
few'.He
continues
in
2006
Nick
Bostrom,
3
director
Future
Humanity
Institute
at
University
Oxford
noted,
"a
lot
cuttingedge
has
filtered
into
general
applications,
often
without
being
called
because
once
something
becomes
useful
enough
common
it's
labelled
anymore".The
term
is
complex
one.Marvin
Minsky
4
it
'suitcase
word'
which
according
him
'is
packed
variously,
depending
on
who
you
ask'.I
don't
claim
understand
world
AI.My
understanding
as
outlined
introduction
UNESCO
Artificial
Intelligence
Gender
Equality
report
5
-'Simply
put,
involves
using
computers
classify,
analyze,
draw
predictions
from
data
sets,
set
rules
algorithms.AI
algorithms
trained
large
datasets
so
they
can
identify
patterns,
make
predictions,
recommend
actions,
figure
out
what
unfamiliar
situations,
learning
new
thus
improving
over
time.The
ability
an
system
improve
automatically
through
experience
known
Machine
Learning
(ML)'.However,
all
pervading
if
believe
some
websites
CEOs
companies
6,7
offered
panacea
range
issues
ending
poverty
reversing
climate
change.There
increasing
body
research
impact
inequality.One
debated
whether
their
applications
may,
least
short
medium
term,
increase
inequality
due
automation.
8,9Research
suggests
AI,
expected
be
