Applied Sciences,
Год журнала:
2024,
Номер
14(23), С. 10899 - 10899
Опубликована: Ноя. 25, 2024
The
main
aim
of
this
study
is
to
investigate
the
opportunities,
challenges,
and
barriers
in
implementing
generative
artificial
intelligence
(Gen
AI)
personalized
patient
care
plans
(PPCPs).
This
systematic
review
paper
provides
a
comprehensive
analysis
current
state,
potential
applications,
opportunities
Gen
AI
settings.
aims
serve
as
key
resource
for
various
stakeholders
such
researchers,
medical
professionals,
data
governance.
We
adopted
PRISMA
methodology
screened
total
247
articles.
After
considering
eligibility
selection
criteria,
we
selected
13
articles
published
between
2021
2024
(inclusive).
criteria
were
based
on
inclusion
studies
that
report
challenges
improving
PPCPs
using
AI.
found
holistic
approach
required
involving
strategy,
communications,
integrations,
collaboration
developers,
healthcare
regulatory
bodies,
patients.
Developing
frameworks
prioritize
ethical
considerations,
privacy,
model
transparency
crucial
responsible
deployment
healthcare.
Balancing
these
requires
wider
create
robust
framework
maximizes
benefits
while
addressing
explainability
models,
validation,
regulation,
privacy
integration
with
existing
clinical
workflows.
Discover Artificial Intelligence,
Год журнала:
2024,
Номер
4(1)
Опубликована: Март 26, 2024
Abstract
Artificial
intelligence
(AI)
is
reshaping
humanity's
future,
and
this
manuscript
provides
a
comprehensive
exploration
of
its
implications,
applications,
challenges,
opportunities.
The
revolutionary
potential
AI
investigated
across
numerous
sectors,
with
focus
on
addressing
global
concerns.
influence
areas
such
as
healthcare,
transportation,
banking,
education
revealed
through
historical
insights
conversations
different
systems.
Ethical
considerations
the
significance
responsible
development
are
addressed.
Furthermore,
study
investigates
AI's
involvement
in
issues
climate
change,
public
health,
social
justice.
This
paper
serves
resource
for
policymakers,
researchers,
practitioners
understanding
complex
link
between
humans.
International Journal of Information and Education Technology,
Год журнала:
2025,
Номер
15(1), С. 90 - 100
Опубликована: Янв. 1, 2025
Technology
can
enhance
the
accessibility
of
higher
education,
providing
equal
opportunities
to
students
from
diverse
backgrounds.
plays
a
crucial
role
in
education
by
revolutionizing
learning
process
and
utilization
educational
resources
students.
The
application
Fuzzy
Comprehensive
Evaluation
(FCE)
significantly
enhances
computational
thinking
skills
improving
instructional
quality,
expanding
scope
objectivity
student
performance
evaluations,
enhancing
assessment
outcomes.
study
involved
919
participants
who
voluntarily
provided
data.
were
selected
using
convenience
sampling,
which
involves
gathering
data
individuals
are
representative
overall
population
willing
participate.
findings
this
suggest
that
self-efficacy
has
substantial
impact
on
skills,
perceived
usefulness,
ease
use,
attitude
towards
using.
Self-efficacy
is
term
used
describe
an
individual’s
belief
their
ability
successfully
handle
various
situations.
usefulness
system
strongly
linked
idea,
pertains
how
much
someone
thinks
it
will
help
them
do
better
called
attitude.
This
research
shows
good
effect
useful
something
seen
be.
Drugs and Drug Candidates,
Год журнала:
2025,
Номер
4(1), С. 9 - 9
Опубликована: Март 4, 2025
Background/Objectives:
The
integration
of
Artificial
Intelligence
(AI)
and
Machine
Learning
(ML)
in
pharmaceutical
research
development
is
transforming
the
industry
by
improving
efficiency
effectiveness
across
drug
discovery,
development,
healthcare
delivery.
This
review
explores
diverse
applications
AI
ML,
emphasizing
their
role
predictive
modeling,
repurposing,
lead
optimization,
clinical
trials.
Additionally,
highlights
AI’s
contributions
to
regulatory
compliance,
pharmacovigilance,
personalized
medicine
while
addressing
ethical
considerations.
Methods:
A
comprehensive
literature
was
conducted
assess
impact
ML
various
domains.
Research
articles,
case
studies,
reports
were
analyzed
examine
AI-driven
advancements
computational
chemistry,
trials,
safety,
supply
chain
management.
Results:
have
demonstrated
significant
research,
including
improved
target
identification,
accelerated
discovery
through
generative
models,
enhanced
structure-based
design
via
molecular
docking
QSAR
modeling.
In
streamlines
patient
recruitment,
predicts
trial
outcomes,
enables
real-time
monitoring.
maintenance,
process
inventory
management
manufacturing
chains.
Furthermore,
has
revolutionized
enabling
precise
treatment
strategies
genomic
data
analysis,
biomarker
diagnostics.
Conclusions:
are
reshaping
offering
innovative
solutions
care.
enhances
outcomes
operational
efficiencies
raising
challenges
that
require
transparent,
accountable
applications.
Future
will
rely
on
collaborative
efforts
ensure
its
responsible
implementation,
ultimately
driving
continued
transformation
sector.
Objective
With
the
digitalization
of
objects
and
spaces,
healthcare
services
are
being
reshaped
globally,
creating
many
potential
applications.
This
study
aimed
to
determine
application
remote
(RHS)
in
a
hospital
by
considering
experiences,
interests,
suggestions
health
professionals,
examples
useful
applications
that
can
be
used,
developed,
or
invented
for
systems.
Methods
A
semi-structured,
face-to-face
interview
survey
was
conducted
with
176
professionals
working
at
Bozok
University.
Results
Branches
highest
practice
experience
were
internal
medicine,
cardiac,
pediatric,
infection,
orthopedics.
Experienced
participants
rated
usability
“Consultation,”
“Support,”
“Monitoring”
higher
than
other
apps,
indicated
they
would
prefer
use
them
themselves
(η²≤0.12).
Requirements
adequacy
lower
older
adults,
internal/surgical
branches,
physicians
groups
(η²
≥
0.05).
Application
categories
showed
significant
relationship
(0.4
≤
r
0.8,
p
<
Several
variables
significantly
explained
models
(p
0.001):
application-usability
(64%),
user-demand
requirements-adequacy
(25%).
Professionals’
demand
(r
=
0.83)
more
strongly
correlated
patient
0.63).
Health
(N
105)
from
17
branches
provided
57
available,
51
developable,
19
innovative
recommendations.
These
coded
according
type,
critical
features,
presence,
integration
status,
usefulness.
Conclusion
RHS’
revealed
demographic
factors
based
on
professionals’
practical
suggestions,
strong,
comprehensive,
up-to-date
methodology.
The
findings
have
international
contribute
implementing
developing
original
medRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 12, 2024
Background:
Generative
Large
language
models
(LLMs)
represent
a
significant
advancement
in
natural
processing,
achieving
state-of-the-art
performance
across
various
tasks.
However,
their
application
clinical
settings
using
real
electronic
health
records
(EHRs)
is
still
rare
and
presents
numerous
challenges.
Objective:
This
study
aims
to
systematically
review
the
use
of
generative
LLMs,
effectiveness
relevant
techniques
patient
care-related
topics
involving
EHRs,
summarize
challenges
faced,
suggest
future
directions.
Methods:
A
Boolean
search
for
peer-reviewed
articles
was
conducted
on
May
19th,
2024
PubMed
Web
Science
include
research
published
since
2023,
which
one
month
after
release
ChatGPT.
The
results
were
deduplicated.
Multiple
reviewers,
including
biomedical
informaticians,
computer
scientists,
physician,
screened
publications
eligibility
data
extraction.
Only
studies
utilizing
LLMs
analyze
EHR
included.
We
summarized
prompt
engineering,
fine-tuning,
multimodal
data,
evaluation
matrices.
Additionally,
we
identified
current
applying
as
reported
by
included
proposed
Results:
initial
6,328
unique
studies,
with
76
screening.
Of
these,
67
(88.2%)
employed
zero-shot
prompting,
five
them
100%
accuracy
specific
Nine
used
advanced
prompting
strategies;
four
tested
these
strategies
experimentally,
finding
that
engineering
improved
performance,
noting
non-linear
relationship
between
number
examples
improvement.
Eight
explored
fine-tuning
all
improvements
tasks,
but
three
noted
potential
degradation
certain
two
utilized
LLM-based
decision-making
enabled
accurate
disease
diagnosis
prognosis.
55
different
metrics
22
purposes,
such
correctness,
completeness,
conciseness.
Two
investigated
LLM
bias,
detecting
no
bias
other
male
patients
received
more
appropriate
suggestions.
Six
hallucinations,
fabricating
names
structured
thyroid
ultrasound
reports.
Additional
not
limited
impersonal
tone
consultations,
made
uncomfortable,
difficulty
had
understanding
responses.
Conclusion:
Our
indicates
few
have
computational
enhance
performance.
diverse
highlight
need
standardization.
currently
cannot
replace
physicians
due
ChatGPT,
developed
by
OpenAI,
is
a
large
language
model
(LLM)
that
leverages
artificial
intelligence
(AI)
and
deep
learning
(DL)
to
generate
human-like
responses.
This
paper
provides
broad,
systematic
review
of
ChatGPT’s
applications
in
healthcare,
particularly
enhancing
patient
engagement
through
medical
history
collection,
symptom
assessment,
decision
support
for
improved
diagnostic
accuracy.
It
assesses
potential
across
multiple
organ
systems
specialties,
highlighting
its
value
clinical,
educational,
administrative
contexts.
analysis
reveals
both
the
benefits
limitations
including
health
literacy
promotion
clinical
decision-making,
alongside
challenges
such
as
risk
inaccuracies,
ethical
considerations
around
informed
consent,
regulatory
hurdles.
A
quantified
summary
key
findings
shows
promise
various
while
underscoring
risks
associated
with
integration
practice.
Through
this
comprehensive
approach,
aims
provide
healthcare
professionals,
researchers,
policymakers
balanced
view
limitations,
emphasizing
need
ongoing
updates
keep
pace
evolving
knowledge.
