Current Opinion in Behavioral Sciences,
Год журнала:
2024,
Номер
58, С. 101397 - 101397
Опубликована: Май 12, 2024
In
this
paper,
we
introduce
a
new
perspective
where
imagination
is
identified
as
the
generativity
of
mental
imagery
and
imaginings,
or
imaginative
(IG),
characterized
by
diverse
array
multisensory
formats,
symbolic
types,
activities
(mental
synthesis).
Reviewing
evidence
spanning
evolution
cognition
in
hominids
some
nonhuman
species,
highlight
significance
IG
Paleolithic
symbolism
findings
from
experimental
studies
behavioral
cognitive
neuroscience
on
perception
imagery.
Our
analysis
also
includes
synthesis
extensive
bibliometric
literature.
We
conclude
that
consciousness
its
phenomenology
rely
vivid
representing,
optimization
strategy
to
navigate
challenges
instability,
ambiguity,
limitations
perception,
memory
consciousness,
crucial
for
survival
adaptation.
review
suggests
imagination,
akin
phenotypic
traits,
plays
critical
role
natural
selection,
highlighting
importance
including
process
variations
within
framework
selection.
not
only
deepens
understanding
evolutionary
development
but
emphasizes
simulation
foresight
key
components
fitness.
Annals of Medicine,
Год журнала:
2023,
Номер
55(1), С. 311 - 318
Опубликована: Янв. 3, 2023
Antimicrobial
resistance
results
from
the
widespread
use
of
antimicrobial
agents
and
is
a
significant
obstacle
to
effectiveness
these
agents.
Numerous
methods
are
used
overcome
this
problem
with
moderate
success.
Besides
efforts
stewards,
several
artificial
intelligence
(AI)-based
technologies
being
explored
for
preventing
development.
These
first-generation
systems
mainly
focus
on
improving
patients'
adherence.
Chronobiology
inherent
in
all
biological
systems.
Host
response
infections
pathogens
activity
assumed
be
affected
by
circadian
clock.
This
paper
describes
reviews
some
current
AI
technologies.
We
present
establishment
second-generation
chronobiology-based
approach
help
further
possibly
existing
resistance.
An
algorithm-controlled
regimen
that
improves
long-term
developed
based
implementation
variability
dosing
drug
administration
times.
The
method
provides
means
ensuring
sustainable
improved
outcomes.
Ongoing
clinical
trials
determine
system
chronic
infections.
Data
studies
expected
shed
light
new
aspect
mechanisms
suggest
overcoming
them.IMPORTANCE
SECTIONThe
presents
resistance.Key
messagesAntimicrobial
agents.We
Biomedicine & Pharmacotherapy,
Год журнала:
2023,
Номер
161, С. 114334 - 114334
Опубликована: Март 9, 2023
Diuretics
are
a
mainstay
therapy
for
congestive
heart
failure
(CHF);
however,
over
one-third
of
patients
develop
diuretic
resistance.
Second-generation
artificial
intelligence
(AI)
systems
introduce
variability
into
treatment
regimens
to
overcome
the
compensatory
mechanisms
underlying
loss
effectiveness
diuretics.
This
open-labeled,
proof-of-concept
clinical
trial
sought
investigate
ability
improve
resistance
by
implementing
algorithm-controlled
therapeutic
regimens.Ten
CHF
with
were
enrolled
in
an
open-labeled
where
Altus
Care™
app
managed
diuretics'
dosage
and
administration
times.
The
provides
personalized
regimen
creating
dosages
times
within
pre-defined
ranges.
Response
was
measured
Kansas
City
Cardiomyopathy
Questionnaire
(KCCQ)
score,
6-minute
walk
test
(SMW),
N-terminal
pro-brain
natriuretic
peptide
(NT-proBNP)
levels,
renal
function.The
second-generation,
AI-based,
alleviated
All
evaluable
demonstrated
improvement
ten
weeks
intervention.
A
dose
reduction
(based
on
three-week
average
before
last
three
intervention)
achieved
7/10
(70
%,
p
=
0.042).
KCCQ
score
improved
9/10
(90
0.002),
SMW
9/9
(100
0.006),
NT-proBNP
decreased
0.02),
serum
creatinine
6/10
(60
0.05).
intervention
associated
reduced
number
emergency
room
visits
CHF-associated
hospitalizations.The
results
support
that
randomization
guided
second-generation
AI
algorithm
improves
response
therapy.
Prospective
controlled
studies
needed
confirm
these
findings.
Current Pharmaceutical Biotechnology,
Год журнала:
2024,
Номер
25(16), С. 2078 - 2088
Опубликована: Янв. 29, 2024
Low
adherence
to
chronic
treatment
regimens
is
a
significant
barrier
improving
clinical
outcomes
in
patients
with
diseases.
result
of
multiple
factors.
Frontiers in Oncology,
Год журнала:
2024,
Номер
14
Опубликована: Июль 30, 2024
Introduction
The
main
obstacle
in
treating
cancer
patients
is
drug
resistance.
Lenvatinib
treatment
poses
challenges
due
to
loss
of
response
and
the
common
dose-limiting
adverse
events
(AEs).
Constrained-disorder-principle
(CDP)-based
second-generation
artificial
intelligence
(AI)
systems
introduce
variability
into
regimens
offer
a
potential
strategy
for
enhancing
efficacy.
This
proof-of-concept
clinical
trial
aimed
assess
impact
personalized
algorithm-controlled
therapeutic
regimen
on
lenvatinib
effectiveness
tolerability.
Methods
A
14-week
open-label,
non-randomized
was
conducted
with
five
receiving
lenvatinib—an
AI-assisted
application
tailored
each
patient,
which
physician
approved.
study
assessed
changes
tumor
through
FDG-PET-CT
markers
quality
life
via
EORTC
QLQ-THY34
questionnaire,
AEs,
laboratory
evaluations.
app
monitored
adherence.
Results
At
14
weeks
follow-up,
disease
control
rate
(including
following
outcomes:
complete
response,
partial
stable
disease)
80%.
scan-based
RECIST
v1.1
PERCIST
criteria
showed
40%
an
additional
patients.
One
patient
experienced
progressing
disease.
Of
participants
thyroid
cancer,
75%
reduction
thyroglobulin
levels,
60%
all
decrease
neutrophil-to-lymphocyte
ratio
during
treatment.
Improvement
median
social
support
score
among
utilizing
system
supports
ancillary
benefit
intervention.
No
grade
4
AEs
or
functional
deteriorations
were
recorded.
Summary
results
this
open-labeled
suggest
that
CDP-based
AI
system-generated
recommendations
may
improve
manageable
AEs.
Prospective
controlled
studies
are
needed
determine
efficacy
approach.
Clinics and Practice,
Год журнала:
2023,
Номер
13(4), С. 994 - 1014
Опубликована: Авг. 20, 2023
The
success
of
artificial
intelligence
depends
on
whether
it
can
penetrate
the
boundaries
evidence-based
medicine,
lack
policies,
and
resistance
medical
professionals
to
its
use.
failure
digital
health
meet
expectations
requires
rethinking
some
challenges
faced.
We
discuss
most
significant
faced
by
patients,
physicians,
payers,
pharmaceutical
companies,
systems
in
world.
goal
healthcare
is
improve
outcomes.
Assisting
diagnosing,
collecting
data,
simplifying
processes
a
"nice
have"
tool,
but
not
essential.
Many
these
have
yet
be
shown
Current
outcome-based
economic
constraints
make
have,"
"assists,"
"ease
processes"
insufficient.
Complex
biological
are
defined
their
inherent
disorder,
bounded
dynamic
boundaries,
as
described
constrained
disorder
principle
(CDP).
It
provides
platform
for
correcting
systems'
malfunctions
regulating
degree
variability.
A
CDP-based
second-generation
system
solutions
faces.
Therapeutic
interventions
held
outcomes
with
systems.
In
addition
improving
clinically
meaningful
endpoints,
algorithms
ensure
patient
physician
engagement
reduce
system's
costs.
Brain Sciences,
Год журнала:
2024,
Номер
14(3), С. 209 - 209
Опубликована: Фев. 23, 2024
There
is
still
controversy
surrounding
the
definition
and
mechanisms
of
consciousness.
The
constrained
disorder
principle
(CDP)
defines
complex
systems
by
their
dynamic
borders,
limiting
inherent
disorder.
In
line
with
CDP,
brain
exhibits
a
bounded
borders
essential
for
proper
function,
efficient
energy
use,
life
support
under
continuous
perturbations.
brain’s
variability
contributes
to
its
adaptability
flexibility.
Neuronal
signal
challenges
association
structures
consciousness
methods
assessing
present
paper
discusses
some
theories
about
consciousness,
emphasizing
failure
explain
variability.
This
describes
how
CDP
accounts
consciousness’s
variability,
complexity,
entropy,
uncertainty.
Using
newly
developed
second-generation
artificial
intelligence
systems,
we
describe
CDP-based
platforms
may
improve
disorders
(DoC)
accounting
platform
could
be
used
response
current
interventions
develop
new
therapeutic
regimens
patients
DoC
in
future
studies.
Journal of Clinical Medicine,
Год журнала:
2024,
Номер
13(11), С. 3325 - 3325
Опубликована: Июнь 5, 2024
Background/Objectives:
Gaucher
Disease
type
1
(GD1)
is
a
recessively
inherited
lysosomal
storage
disorder
caused
by
deficiency
in
the
enzyme
β-glucocerebrosidase.
Enzyme
replacement
therapy
(ERT)
has
become
standard
of
care
for
patients
with
GD.
However,
over
10%
experience
an
incomplete
response
or
partial
loss
to
ERT,
necessitating
exploration
alternative
approaches
enhance
treatment
outcomes.
The
present
feasibility
study
aimed
determine
using
second-generation
artificial
intelligence
(AI)
system
that
introduces
variability
into
dosing
regimens
ERT
improve
and
potentially
overcome
enzyme.
Methods:
This
was
open-label,
prospective,
single-center
proof-of-concept
study.
Five
GD1
who
received
were
enrolled.
used
Altus
Care™
cellular-phone-based
application,
which
incorporated
algorithm-based
approach
offer
random
within
pre-defined
range
set
physician.
app
enabled
personalized
therapeutic
variations
dosages
administration
times.
Results:
AI-based
regimen
associated
stable
responses
GD1.
SF-36
quality
life
scores
improved
one
patient,
sense
change
health
two;
platelet
levels
increased
two
patients,
hemoglobin
remained
stable.
demonstrated
high
engagement
rate
among
caregivers,
showing
compliance
regimen.
Conclusions:
highlights
potential
variability-based
effectiveness
GD
calls
further
longer
trials
validate
these
findings.
