Turning back the clock: reintroducing ‘SAFE’ principles to spinal cord stimulation for long-term therapy preservation
Pain Management,
Journal Year:
2025,
Volume and Issue:
unknown, P. 1 - 3
Published: Jan. 21, 2025
Language: Английский
Clinical and Operational Applications of Artificial Intelligence and Machine Learning in Pharmacy: A Narrative Review of Real-World Applications
Pharmacy,
Journal Year:
2025,
Volume and Issue:
13(2), P. 41 - 41
Published: March 7, 2025
Over
the
past
five
years,
application
of
artificial
intelligence
(AI)
including
its
significant
subset,
machine
learning
(ML),
has
significantly
advanced
pharmaceutical
procedures
in
community
pharmacies,
hospital
and
industry
settings.
Numerous
notable
healthcare
institutions,
such
as
Johns
Hopkins
University,
Cleveland
Clinic,
Mayo
have
demonstrated
measurable
advancements
use
delivery.
Community
pharmacies
seen
a
40%
increase
drug
adherence
55%
reduction
missed
prescription
refills
since
implementing
technologies.
According
to
reports,
implementations
reduced
distribution
errors
by
up
75%
enhanced
detection
adverse
medication
reactions
65%.
businesses,
Atomwise
Insilico
Medicine,
assert
that
they
made
noteworthy
progress
creation
AI-based
medical
therapies.
Emerging
technologies
like
federated
quantum
computing
potential
boost
prediction
protein–drug
interactions
300%,
despite
challenges
high
implementation
costs
regulatory
compliance.
The
significance
upholding
patient-centred
care
while
encouraging
technology
innovation
is
emphasised
this
review.
Language: Английский
Beyond TKIs: Advancing Therapeutic Frontiers with Immunotherapy, Targeted Agents, and Combination Strategies in Resistant Chronic Myeloid Leukemia
Hemato,
Journal Year:
2025,
Volume and Issue:
6(1), P. 6 - 6
Published: March 11, 2025
Background:
Chronic
myeloid
leukemia
(CML)
relates
to
the
abnormal
presence
of
Philadelphia
chromosome,
which
originates
production
BCR-ABL1
fusion
protein
and
therefore
leads
neoplastic
transformation
unregulated
cell
growth.
The
advent
tyrosine
kinase
inhibitors
(TKIs)
has
resulted
in
tremendous
improvements
CML
scenarios;
however,
there
are
practical
difficulties,
especially
considering
late
stages
disease.
This
review
examines
recently
developed
strategies
that
intended
increase
efficiency
treatment
by
overcoming
TKI
resistance.
Methods:
We
performed
a
literature
such
databases
as
PubMed,
Scopus,
Web
Science,
Embase
for
last
ten
years.
following
keywords
were
used
studies:
‘CML’,
‘TKI
resistance’,
‘novel
therapies’,
‘immunotherapy’,
‘targeted
agents’,
‘combination
therapies’.
Only
those
studies
included
clinical
trials
preclinical
across-the-board
developmental
programs
attempt
target
tumor
at
multiple
levels
not
just
focus
on
basic
first-line
TKIs.
Results:
In
patients
who
do
respond
TKIs,
novel
therapeutics
encompass
ponatinib,
asciminib,
CAR-T
immunotherapy,
BCL-2
mTOR
inhibition
conjunction
with
therapy.
addresses
both
BCR-ABL1-dependent
independent
resistance
mechanisms,
increasing
chance
achieving
deeper
molecular
response
reduced
toxicity.
Nonetheless,
they
exhibit
diverse
characteristics
regarding
efficacy,
safety,
cost,
quality
life
effects.
Discussion:
numerous
challenges
remain
understanding
mechanisms
resistance,
long-term
efficacy
medicines,
ideal
combinations
attain
optimal
outcomes.
Areas
future
research
include
search
other
patterns
tailoring
specific
treatments
patients,
incorporating
AI
improve
diagnosis
monitoring.
Conclusion:
introduction
therapeutic
techniques
into
practice
needs
collaborative
approach
persistent
dynamism
new
findings
from
research.
Our
analysis
indicates
posed
resistant
disease
complex
require
further
protocol
development.
Language: Английский
Adoption barriers and facilitators of wearable health devices with AI integration: a patient-centred perspective
Frontiers in Medicine,
Journal Year:
2025,
Volume and Issue:
12
Published: April 3, 2025
Wearable
devices
that
incorporate
artificial
intelligence
(AI)
have
revolutionised
healthcare
through
continuous
monitoring,
early
detection,
and
tailored
management
of
chronic
diseases.
This
cross-sectional
study
analysed
patients'
perceptions,
trust,
awareness
AI-driven
wearable
health
technologies,
emphasising
the
identification
primary
facilitators
barriers
to
adoption.
A
total
455
participants,
comprising
individuals
with
conditions,
were
recruited
convenience
stratified
sampling
methods.
Data
collected
via
an
online
questionnaire
included
demographic
questions,
Likert-scale
items,
multiple-choice
questions
evaluate
particular
AI
features
functionalities
devices.
The
findings
indicated
predominantly
positive
most
participants
concurring
improve
proactive
care,
facilitate
remote
consultations,
deliver
precise
insights.
Concerns
regarding
technical
failures,
data
accuracy,
potential
reduction
human
interaction
significant.
No
notable
differences
identified;
however,
conditions
expressed
more
favourable
perceptions.
research
emphasises
necessity
user
education,
reliability,
professional
oversight
for
successful
integration
AI-powered
wearables
in
Language: Английский
Shaping the future of geriatric chronic pain care: a research agenda for progress
Pain Management,
Journal Year:
2025,
Volume and Issue:
unknown, P. 1 - 13
Published: April 17, 2025
Chronic
pain
is
highly
prevalent
among
older
adults
and
its
burden
will
become
increasingly
significant
as
our
population
ages.
Yet,
chronic
often
undertreated
in
this
vulnerable
due
to
various
barriers
health
care
delivery.
To
improve
geriatric
management,
we
assert
that
require
a
dedicated
research
agenda
designed
inform
the
development,
testing,
implementation
of
treatments
account
for
unique
vulnerabilities
healthcare
needs
population.
Specifically,
propose
following
four
areas
immediate
attention
better
serve
with
pain:
(1)
equity,
(2)
substance
use,
(3)
dyadic
interventions,
(4)
digital
health.
Our
proposed
aims
create
more
robust
comprehensive
body
evidence
ultimately
transform
advance
management.
Language: Английский
A roadmap for artificial intelligence in pain medicine: current status, opportunities, and requirements
Current Opinion in Anaesthesiology,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 24, 2025
Purpose
of
review
Artificial
intelligence
(AI)
represents
a
transformative
opportunity
for
pain
medicine,
offering
potential
solutions
to
longstanding
challenges
in
assessment
and
management.
This
synthesizes
the
current
state
AI
applications
with
strategic
framework
implementation,
highlighting
established
adaptation
pathways
from
adjacent
medical
fields.
Recent
findings
In
acute
pain,
systems
have
achieved
regulatory
approval
ultrasound
guidance
regional
anesthesia
shown
promise
automated
scoring
through
facial
expression
analysis.
For
chronic
management,
machine
learning
algorithms
improved
diagnostic
accuracy
musculoskeletal
conditions
enhanced
treatment
selection
predictive
modeling.
Successful
integration
requires
interdisciplinary
collaboration
physician
coleadership
throughout
development
process,
specific
adaptations
needed
pain-specific
challenges.
Summary
roadmap
outlines
comprehensive
methodological
emphasizing
four
key
phases:
problem
definition,
algorithm
development,
validation,
implementation.
Critical
areas
future
include
perioperative
trajectory
prediction,
real-time
procedural
guidance,
personalized
optimization.
Success
ultimately
depends
on
maintaining
strong
partnerships
between
clinicians,
developers,
researchers
while
addressing
ethical,
regulatory,
educational
considerations.
Language: Английский
Challenges, Limitations, and Ethical Considerations of AI in Immunology and Healthcare
Diego Rajchenberg,
No information about this author
Rodrigo Hess,
No information about this author
Marvin Paulo Lins
No information about this author
et al.
Advances in computational intelligence and robotics book series,
Journal Year:
2025,
Volume and Issue:
unknown, P. 393 - 426
Published: May 2, 2025
Artificial
Intelligence
(AI)
is
transforming
immunology
and
healthcare
by
enabling
advanced
diagnostics,
personalized
treatments,
data-driven
decision-making.
However,
its
implementation
fraught
with
challenges,
including
the
complexity
of
immune
networks,
variability
in
patient
responses,
data
quality
issues.
AI
models
often
struggle
to
understand
variations
that
occur
among
diverse
human
populations
adapt
dynamic
concepts
immunology.
Ethical
concerns,
such
as
privacy,
informed
consent,
algorithmic
bias,
further
complicate
integration
into
clinical
practice.
Logistical
barriers,
resource
constraints
regulatory
hurdles,
limit
accessibility,
especially
low-resource
settings,
although
it
has
potential
diminish
inequalities
access
care
medical
information.
This
chapter
explores
these
challenges
while
emphasizing
solutions,
interdisciplinary
collaboration,
adaptive
frameworks,
equitable
sharing,
maximize
AI's
advancing
immunological
research
global
outcomes.
Language: Английский
Transforming Chronic Pain Management: Integrating Neuromodulation with Advanced Technologies to Tackle Cognitive Dysfunction – A Narrative Review
Journal of Pain Research,
Journal Year:
2025,
Volume and Issue:
Volume 18, P. 2497 - 2507
Published: May 1, 2025
Chronic
pain
is
a
complex
and
multidimensional
condition
that
disrupts
both
physical
function
cognitive
processing,
creating
bidirectional
cycle
amplifies
symptom
burden
complicates
clinical
management.
Cognitive
dysfunction,
characterized
by
deficits
in
memory,
attention,
executive
function,
further
impairs
treatment
adherence
functional
recovery.
Conventional
pharmacologic
therapies
frequently
fail
to
address
this
dual
are
associated
with
adverse
effects,
including
dependence
impairment.
Neuromodulation
has
emerged
as
promising
nonpharmacologic
alternative,
capable
of
modulating
neuroplastic,
neuroinflammatory,
neurotransmitter
pathways
implicated
decline.
This
narrative
review
examines
the
mechanisms
applications
spinal
cord
stimulation
(SCS),
transcutaneous
electrical
nerve
(TENS),
neuromuscular
(NMES),
evaluates
emerging
innovations
such
EcoAI™,
an
artificial
intelligence-driven,
non-invasive
neuromodulation
platform.
By
integrating
physiological
behavioral
biomarkers
real-time
adaptive
therapy,
EcoAI
similar
technologies
represent
shift
toward
personalized,
precision-based
interventions.
Additional
advances
remote
patient
monitoring
(RPM)
closed-loop
feedback
systems
enhance
therapeutic
responsiveness
continuity
care.
Collectively,
these
approaches
offer
scalable,
patient-centered
framework
for
managing
chronic
its
comorbidities.
Future
priorities
include
development
validated
biomarkers,
rigorous
evaluation
AI-integrated
systems,
equitable
implementation
strategies
ensure
broad
access
next-generation
neuromodulation.
Language: Английский
Perspectives of people with diabetes on AI-integrated wearable devices: perceived benefits, barriers, and opportunities for self-management
Frontiers in Medicine,
Journal Year:
2025,
Volume and Issue:
12
Published: April 23, 2025
Wearable
devices
that
incorporate
artificial
intelligence
(AI)
have
become
effective
instruments
for
managing
diabetes
through
real-time
monitoring,
improved
adherence,
and
increased
person
with
engagement.
Person
perceptions,
adoption
barriers,
preferences
critically
impact
the
effectiveness
widespread
utilisation
of
these
technologies.
The
aim
study
was
to
investigate
perceptions
people
regarding
wearable
devices,
emphasising
their
perceived
advantages,
challenges,
potential
role
in
facilitating
self-management.
A
cross-sectional
involving
418
conducted,
participants
recruited
via
online
platforms
groups.
Data
were
gathered
a
structured
questionnaire
included
Likert-scale
items,
multiple-choice
questions,
open-ended
responses.
Descriptive
statistics
employed
analyse
quantitative
data,
whereas
qualitative
responses
underwent
thematic
analysis
discern
key
trends.
Participants
demonstrated
significant
awareness
primary
functions
83.9%
acknowledging
utility
monitoring
glucose
levels
physical
activity.
advantages
comprised
adherence
medication
regimens
(81.9%)
heightened
confidence
management
(82.1%).
Significant
barriers
identified,
including
data
privacy
concerns
(79.7%),
cost
issues
(77.0%),
usability
challenges
(75.1%).
Thematic
indicated
demand
features
actionable
feedback,
integration
healthcare
providers,
enhanced
usability.
Despite
81.9%
willingness
adopt
AI-integrated
if
recommended
by
providers.
findings
indicate
regard
as
condition,
especially
terms
support.
Concerns
privacy,
cost,
device
must
be
addressed
enhance
rates.
These
insights
can
inform
development
patient-centered
guide
strategies
technologies
into
care.
Language: Английский