Annals of the Russian academy of medical sciences,
Год журнала:
2024,
Номер
79(4), С. 346 - 352
Опубликована: Окт. 10, 2024
Artificial
intelligence
(AI)
in
healthcare
can
be
used
to
solve
a
wide
range
of
tasks,
such
as
diagnosis,
treatment
and
self-monitoring
patients.
This
review
is
devoted
the
problem
polypharmacotherapy,
development
adverse
drug
reactions
consequence
it
use
AI
this
field.
allows
analyze
interactions,
identify
possible
suggest
optimal
combinations
drugs
regimen.
The
clinical
decision
support
systems,
which
are
developed
various
countries,
has
shown
improved
efficiency
doctor’s
work
increased
patient’s
safety
with
help
AI.
polypharmacotherapy
requires
further
research
improve
software
products
that
would
allow
evaluating
not
only
paired,
but
also
multiple
interactions.
The
influence
of
artificial
intelligence
(AI)
has
drastically
risen
in
recent
years,
especially
the
field
medicine.
Its
spread
so
greatly
that
it
is
determined
to
become
a
pillar
future
medical
world.
A
comprehensive
literature
search
related
AI
healthcare
was
performed
PubMed
database
and
retrieved
relevant
information
from
suitable
ones.
excels
aspects
such
as
rapid
adaptation,
high
diagnostic
accuracy,
data
management
can
help
improve
workforce
productivity.
With
this
potential
sight,
FDA
continuously
approved
more
machine
learning
(ML)
software
be
used
by
workers
scientists.
However,
there
are
few
controversies
increased
chances
breaches,
concern
for
clinical
implementation,
dilemmas.
In
article,
positive
negative
implementation
discussed,
well
recommended
some
solutions
issues
at
hand.
JACCP JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 13, 2025
Abstract
There
is
a
need
to
understand
contemporary
scientific
advances
as
clinical
pharmacy
evolves.
One
rapidly
expanding
area
artificial
intelligence
(AI),
which
has
grown
significantly
over
the
past
year
because
of
public
availability
large
language
models.
This
commentary
reviews
published
literature
describing
and
evaluating
applications
AI
each
aspect
medication
use
process
forecasts
potential
future
roles
for
in
practice.
Potential
challenges
implementation
are
also
described.
Healthcare,
Год журнала:
2024,
Номер
12(7), С. 788 - 788
Опубликована: Апрель 5, 2024
Prescribing
medications
is
a
fundamental
practice
in
the
management
of
illnesses
that
necessitates
in-depth
knowledge
clinical
pharmacology.
Polypharmacy,
or
concurrent
use
multiple
by
individuals
with
complex
health
conditions,
poses
significant
challenges,
including
an
increased
risk
drug
interactions
and
adverse
reactions.
The
Saudi
Vision
2030
prioritises
enhancing
healthcare
quality
safety,
addressing
polypharmacy.
Artificial
intelligence
(AI)
offers
promising
tools
to
optimise
medication
plans,
predict
reactions
ensure
safety.
This
review
explores
AI’s
potential
revolutionise
polypharmacy
Arabia,
highlighting
practical
applications,
challenges
path
forward
for
integration
AI
solutions
into
practices.
JMIR Medical Informatics,
Год журнала:
2024,
Номер
12, С. e59258 - e59258
Опубликована: Июль 5, 2024
Background
Reading
medical
papers
is
a
challenging
and
time-consuming
task
for
doctors,
especially
when
the
are
long
complex.
A
tool
that
can
help
doctors
efficiently
process
understand
needed.
Objective
This
study
aims
to
critically
assess
compare
comprehension
capabilities
of
large
language
models
(LLMs)
in
accurately
understanding
research
using
STROBE
(Strengthening
Reporting
Observational
Studies
Epidemiology)
checklist,
which
provides
standardized
framework
evaluating
key
elements
observational
study.
Methods
The
methodological
type
research.
evaluate
new
generative
artificial
intelligence
tools
papers.
novel
benchmark
pipeline
processed
50
from
PubMed,
comparing
answers
6
LLMs
(GPT-3.5-Turbo,
GPT-4-0613,
GPT-4-1106,
PaLM
2,
Claude
v1,
Gemini
Pro)
established
by
expert
professors.
Fifteen
questions,
derived
assessed
LLMs’
different
sections
paper.
Results
exhibited
varying
performance,
with
GPT-3.5-Turbo
achieving
highest
percentage
correct
(n=3916,
66.9%),
followed
GPT-4-1106
(n=3837,
65.6%),
2
(n=3632,
62.1%),
v1
(n=2887,
58.3%),
Pro
(n=2878,
49.2%),
GPT-4-0613
(n=2580,
44.1%).
Statistical
analysis
revealed
statistically
significant
differences
between
(P<.001),
older
showing
inconsistent
performance
compared
newer
versions.
showcased
distinct
performances
each
question
across
parts
scholarly
paper—with
certain
like
GPT-3.5
remarkable
versatility
depth
understanding.
Conclusions
first
retrieval
augmented
generation
method.
findings
highlight
potential
enhance
improving
efficiency
facilitating
evidence-based
decision-making.
Further
needed
address
limitations
such
as
influence
formats,
biases,
rapid
evolution
LLM
models.
Pharmaceuticals,
Год журнала:
2024,
Номер
17(3), С. 395 - 395
Опубликована: Март 19, 2024
Adverse
drug
reactions
continue
to
be
not
only
one
of
the
most
urgent
problems
in
clinical
medicine,
but
also
a
social
problem.
The
aim
this
study
was
bibliometric
analysis
use
digital
technologies
prevent
adverse
and
an
overview
their
main
applications
improve
safety
pharmacotherapy.
search
conducted
using
Web
Science
database
for
period
1991–2023.
A
positive
trend
publications
field
management
revealed.
total
72%
all
relevant
come
from
following
countries:
USA,
China,
England,
India,
Germany.
Among
organizations
active
side
effect
technologies,
American
Chinese
universities
dominate.
Visualization
publication
keywords
VOSviewer
software
1.6.18
revealed
four
clusters:
“preclinical
studies”,
“clinical
trials”,
“pharmacovigilance”,
“reduction
order
patient’s
quality
life”.
Molecular
design
virtual
models
toxicity
modeling,
data
integration,
repurposing
are
among
key
tools
used
preclinical
research
phase.
Integrating
application
machine
learning
algorithms
analysis,
monitoring
electronic
databases
spontaneous
messages,
medical
records,
scientific
databases,
networks,
device
into
trials
pharmacovigilance
systems,
can
significantly
efficiency
development,
implementation,
processes.
result
combining
these
is
huge
synergistic
provision
up-to-date
valuable
information
healthcare
professionals,
patients,
health
authorities.
Drug Development and Industrial Pharmacy,
Год журнала:
2025,
Номер
unknown, С. 1 - 34
Опубликована: Фев. 18, 2025
As
the
global
demographic
shifts
towards
an
aging
society,
geriatric
patient
population
is
steadily
increasing.
These
patients
often
suffer
from
comorbidities
and
require
numerous
oral
medications,
which
can
be
especially
challenging
for
dysphagic
patients.
Mucoadhesive
buccal
films
seems
promising
could
reduce
pill
burden,
simplify
administration,
enable
individualised
drug
therapy.
This
review
aims
to
explore
age-related
changes
in
cavity
their
impact
on
mucoadhesive
film
delivery,
including
potential
strategies
overcome
these
barriers
delivery.
It
was
observed
that
impacts
mucosa
as
well
properties
of
saliva.
There
are
several
studies
application
use
a
wide
range
permeation
enhancers.
The
3D
printing
introduce
dosing
flexibility
manufacturing.
Interdisciplinary Perspectives on Infectious Diseases,
Год журнала:
2025,
Номер
2025(1)
Опубликована: Янв. 1, 2025
This
paper
explores
the
transformative
potential
of
integrating
artificial
intelligence
(AI)
in
diagnosis
and
prognosis
infectious
diseases.
By
analyzing
diverse
datasets,
including
clinical
symptoms,
laboratory
results,
imaging
data,
AI
algorithms
can
significantly
enhance
early
detection
personalized
treatment
strategies.
reviews
how
AI-driven
models
improve
diagnostic
accuracy,
predict
patient
outcomes,
contribute
to
effective
disease
management.
It
also
addresses
challenges
ethical
considerations
associated
with
AI,
data
privacy,
algorithmic
bias,
equitable
access
healthcare.
Highlighting
case
studies
recent
advancements,
underscores
AI's
role
revolutionizing
management
its
implications
for
future
healthcare
delivery.
Expert Opinion on Drug Safety,
Год журнала:
2025,
Номер
unknown, С. 1 - 12
Опубликована: Апрель 2, 2025
The
main
purpose
of
this
study
is
to
observe
and
detect
adverse
reactions
the
combination
topotecan,
bevacizumab
cyclophosphamide,
learn
more
about
possible
drug
(ADRs)
help
doctors
make
right
medication
decisions
treatment
plans.
Adverse
event
signals
were
detected
quantified
using
data
from
U.S.
Food
Drug
Administration's
Event
Reporting
System
reporting
ratios,
proportions
reports
(PRR),
Bayesian
Confidence
Propagation
Neural
Networks
(BCPN),
empirical
Geometric
Mean
(EBGM).
Subgroup
analyses
performed
compare
events
associated
with
topotecan
alone.
analysis
FAERS
revealed
a
total
1,789
primary
suspected
(PS
AEs)
linked
topotecan.
Weibull
shape
parameter
(β)
for
females
was
lower
than
males
across
all
age
groups,
indicating
potentially
higher
susceptibility
effects
in
female
patients.
This
proved
several
expected
new
bevacizumab,
cyclophosphamide.
While
some
ADRs,
such
as
neutropenia
anemia,
align
known
profile
detection
novel
signals,
including
potential
gender-based
differences
response,
warrants
further
investigation.
