Physiology,
Journal Year:
2023,
Volume and Issue:
unknown
Published: July 13, 2023
The
role
of
the
autonomic
nervous
system
(ANS)
in
chronic
pain
(CP)
and
its
chronicity
is
considered
secondary
reactive
to
nociceptive
processes
somatic
(SomNS).
However,
research
clinical
data
strongly
suggest
opposite.
ANS
an
ancient,
complex
ample
part
system.
It
serves
controls
visceral
organs
tissues.
takes
all
aspects
types
influences
mechanisms
at
both
peripheral
central
levels.
In
this
chapter
we
bring
together
evidence
from
biomedical
disciplines
practice
support
alternative
theory
which
contradicts
traditional
views
on
subject.
We
also
raise
questions
require
further
consolidate
facts,
advance
our
knowledge
improve
treatment
strategies
for
CP.
importance
topic
difficult
overestimate
because
significant
impact
CP
society
lack
understanding,
efficient
therapy
or
cure.
Journal of Medicine Surgery and Public Health,
Journal Year:
2024,
Volume and Issue:
3, P. 100099 - 100099
Published: April 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.
Journal of Medical Internet Research,
Journal Year:
2024,
Volume and Issue:
26, P. e51250 - e51250
Published: April 12, 2024
Background
The
continuous
monitoring
and
recording
of
patients’
pain
status
is
a
major
problem
in
current
research
on
postoperative
management.
In
the
large
number
original
or
review
articles
focusing
different
approaches
for
assessment,
many
researchers
have
investigated
how
computer
vision
(CV)
can
help
by
capturing
facial
expressions.
However,
there
lack
proper
comparison
results
between
studies
to
identify
gaps.
Objective
purpose
this
systematic
meta-analysis
was
investigate
diagnostic
performance
artificial
intelligence
models
multilevel
assessment
from
images.
Methods
PubMed,
Embase,
IEEE,
Web
Science,
Cochrane
Library
databases
were
searched
related
publications
before
September
30,
2023.
Studies
that
used
images
alone
estimate
multiple
values
included
review.
A
study
quality
conducted
using
Quality
Assessment
Diagnostic
Accuracy
Studies,
2nd
edition
tool.
these
assessed
metrics
including
sensitivity,
specificity,
log
odds
ratio
(LDOR),
area
under
curve
(AUC).
intermodal
variability
presented
forest
plots.
Results
total
45
reports
reported
test
accuracies
ranged
0.27-0.99,
other
metrics,
mean
standard
error
(MSE),
absolute
(MAE),
intraclass
correlation
coefficient
(ICC),
Pearson
(PCC),
0.31-4.61,
0.24-2.8,
0.19-0.83,
0.48-0.92,
respectively.
total,
6
meta-analysis.
Their
combined
sensitivity
98%
(95%
CI
96%-99%),
specificity
97%-99%),
LDOR
7.99
6.73-9.31),
AUC
0.99
0.99-1).
subgroup
analysis
showed
acceptable,
although
imbalanced
data
still
emphasized
as
problem.
All
had
at
least
one
domain
with
high
risk
bias,
20%
(9/45)
studies,
no
applicability
concerns.
Conclusions
This
summarizes
recent
evidence
automatic
estimation
expressions
compared
accuracy
Promising
established
CV
algorithms.
Weaknesses
also
identified,
suggesting
larger
evaluating
multiclass
classification
could
improve
future
studies.
Trial
Registration
PROSPERO
CRD42023418181;
https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=418181
Frontiers in Digital Health,
Journal Year:
2025,
Volume and Issue:
6
Published: Jan. 28, 2025
Introduction
Artificial
intelligence
(AI)
models
trained
on
audio
data
may
have
the
potential
to
rapidly
perform
clinical
tasks,
enhancing
medical
decision-making
and
potentially
improving
outcomes
through
early
detection.
Existing
technologies
depend
limited
datasets
collected
with
expensive
recording
equipment
in
high-income
countries,
which
challenges
deployment
resource-constrained,
high-volume
settings
where
a
profound
impact
health
equity.
Methods
This
report
introduces
novel
protocol
for
collection
corresponding
application
that
captures
information
guided
questions.
Results
To
demonstrate
of
Voice
EHR
as
biomarker
health,
initial
experiments
quality
multiple
case
studies
are
presented
this
report.
Large
language
(LLMs)
were
used
compare
transcribed
(from
same
patients)
conventional
techniques
like
choice
Information
contained
samples
was
consistently
rated
equally
or
more
relevant
evaluation.
Discussion
The
HEAR
facilitates
an
electronic
record
(“Voice
EHR”)
contain
complex
biomarkers
from
voice/respiratory
features,
speech
patterns,
spoken
semantic
meaning
longitudinal
context–potentially
compensating
typical
limitations
unimodal
datasets.
Frontiers in Digital Health,
Journal Year:
2025,
Volume and Issue:
7
Published: April 15, 2025
Bridge2AI-Voice,
a
collaborative
multi-institutional
consortium,
aims
to
generate
large-scale,
ethically
sourced
voice,
speech,
and
cough
database
linked
health
metadata
in
order
support
AI-driven
research.
A
novel
smartphone
application,
the
Bridge2AI-Voice
app,
was
created
collect
standardized
recordings
of
acoustic
tasks,
validated
patient
questionnaires,
reported
outcomes.
Before
broad
data
collection,
feasibility
study
undertaken
assess
viability
app
clinical
setting
through
task
performance
metrics
participant
feedback.
Participants
were
recruited
from
tertiary
academic
voice
center.
instructed
complete
series
tasks
application
on
an
iPad.
The
Plan-Do-Study-Act
model
for
quality
improvement
implemented.
Data
collected
included
demographics
including
time
completion,
successful
task/recording
need
assistance.
Participant
feedback
measured
by
qualitative
interview
adapted
Mobile
App
Rating
Scale.
Forty-seven
participants
enrolled
(61%
female,
92%
primary
language
English,
mean
age
58.3
years).
All
owned
smart
devices,
with
49%
using
mobile
apps.
Overall
completion
rate
68%,
successfully
recorded
41%
cases.
requested
assistance
completed
challenges
mainly
related
design
instruction
understandability.
Interview
responses
reflected
favorable
perception
voice-screening
apps
their
features.
Findings
suggest
that
is
promising
tool
acquisition
setting.
However,
development
improved
User
Interface/User
Experience
broader,
diverse
studies
are
needed
usable
tool.Level
evidence:
3.
Scientifica,
Journal Year:
2025,
Volume and Issue:
2025(1)
Published: Jan. 1, 2025
Background:
Pain
is
a
significant
symptom
in
cancer
patients
that
frequently
not
effectively
treated,
and
managing
it
seen
as
crucial
aspect
of
caring
for
these
patients.
This
severe
pain
causes
disturbance
their
quality
life.
At
present,
there
are
different
challenges
utilizing
range
pharmacological
nonpharmacological
treatments
Recent
technological
advancements,
particularly
artificial
intelligence,
have
improved
the
management
Artificial
intelligence
its
algorithms
offer
potential
solutions
relief
with
reduced
side
effects.
Study
Design:
The
current
review
aimed
to
assess
validity
studies
on
using
Four
databases
been
used
all
published
from
start
2023:
PubMed,
Scopus,
Web
Science,
Google
Scholar.
search
mechanism
articles
was
mainly
valid
mesh-based
keywords,
asking
experts,
reviewing
literature
including
"Pain,"
"Pain
management,"
"Cancer,"
"Artificial
intelligence."
During
initial
search,
total
450
were
found,
after
considering
inclusion
exclusion
criteria
abstract
content
articles,
15
finally
included
study.
Results:
AI-based
can
provide
individual
plans.
When
AI
analyzes
large
patient
data
such
physiological
signals,
responses
treatment,
symptoms
who
diagnosed
pain,
possible
accurately
adjust
therapeutic
measures.
Conclusions:
enables
healthcare
providers
timely
care
assistance
through
remote
monitoring
telehealth
services,
even
when
they
physically
present.
Despite
presence
hurdles
ensuring
ethical
practices
protecting
privacy,
integration
oncology
brings
optimism
future.
Depression and Anxiety,
Journal Year:
2025,
Volume and Issue:
2025(1)
Published: Jan. 1, 2025
Depression
accounts
for
a
major
share
of
global
disability‐adjusted
life‐years
(DALYs).
Diagnosis
typically
requires
psychiatrist
or
lengthy
self‐assessments,
which
can
be
challenging
symptomatic
individuals.
Developing
reliable,
noninvasive,
and
accessible
detection
methods
is
healthcare
priority.
Voice
analysis
offers
promising
approach
early
depression
detection,
potentially
improving
treatment
access
reducing
costs.
This
paper
presents
novel
pipeline
that
addresses
several
critical
challenges
in
the
field,
including
data
imbalance,
label
quality,
model
generalizability.
Our
study
utilizes
high‐quality,
high‐depression‐prevalence
dataset
collected
from
specialized
chronic
pain
clinic,
enabling
robust
even
with
limited
sample
size.
We
obtained
lift
accuracy
up
to
15%
over
50–50
baseline
our
52‐patient
using
3‐fold
cross‐validation
test
(which
means
train
set
n
=
34,
std
2.8%,
p
‐value
0.01).
further
show
combining
voice‐only
acoustic
features
single
self‐report
question
(subject
unit
distress
[SUDs])
significantly
improves
predictive
accuracy.
While
relying
on
SUDs
not
always
good
practice,
collection
setting
lacked
incentives
misrepresent
status;
were
highly
giving
86%
accuracy;
adding
raises
it
92%,
exceeding
stand‐alone
potential
0.1.
Further
will
enhance
accuracy,
supporting
rapid,
noninvasive
method
overcomes
clinical
barriers.
These
findings
offer
tool
across
settings.
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(7), P. 3064 - 3064
Published: April 7, 2024
One
of
the
central
social
challenges
21st
century
is
society’s
aging.
AI
provides
numerous
possibilities
for
meeting
this
challenge.
In
context,
concept
digital
twins,
based
on
Cyber-Physical
Systems,
offers
an
exciting
prospect.
The
e-VITA
project,
in
which
a
virtual
coaching
system
elderly
people
being
created,
allows
same
to
be
assessed
as
model
development.
This
white
paper
collects
and
presents
relevant
findings
from
research
areas
around
twin
technologies.
Furthermore,
we
address
ethical
issues.
shows
that
twins
can
usefully
applied
older
adults.
However,
it
also
required
technologies
must
further
developed
issues
discussed
appropriate
framework.
Finally,
explains
how
project
could
pave
way
towards
developing
Digital
Twin
Ageing.
Frontiers in Computer Science,
Journal Year:
2024,
Volume and Issue:
6
Published: July 29, 2024
Accurate
pain
detection
is
a
critical
challenge
in
healthcare,
where
communication
and
interpretation
of
often
limit
traditional
subjective
assessments.
The
current
situation
characterized
by
the
need
for
more
objective
reliable
methods
to
assess
pain,
especially
patients
who
cannot
effectively
communicate
their
experiences,
such
as
young
children
or
critically
ill
individuals.
Despite
technological
advances,
effective
integration
artificial
intelligence
tools
multifaceted
accurate
continues
present
significant
challenges.
Our
proposal
addresses
this
problem
through
an
interdisciplinary
approach,
developing
hybrid
model
that
combines
analysis
facial
gestures
paralanguage
using
techniques.
This
contributes
significantly
field,
allowing
objective,
accurate,
sensitive
individual
variations.
results
obtained
have
been
notable,
with
our
achieving
precision
92%,
recall
90%,
specificity
95%,
demonstrating
evident
efficiency
over
conventional
methodologies.
clinical
implications
include
possibility
improving
assessment
various
medical
settings,
faster
interventions,
thereby
patients’
quality
life.
