Sensors,
Год журнала:
2023,
Номер
23(23), С. 9597 - 9597
Опубликована: Дек. 4, 2023
Coronavirus
has
caused
many
casualties
and
is
still
spreading.
Some
people
experience
rapid
deterioration
that
mild
at
first.
The
aim
of
this
study
to
develop
a
prediction
model
for
COVID-19
patients
during
the
isolation
period.
We
collected
vital
signs
from
wearable
devices
clinical
questionnaires.
derivation
cohort
consisted
diagnosed
with
between
September
December
2021,
external
validation
March
June
2022.
To
model,
total
50
participants
wore
device
an
average
77
h.
evaluate
181
infected
65
designed
machine
learning-based
models
predict
in
COVID-19.
10
min
advance,
showed
area
under
receiver
characteristic
curve
(AUC)
0.99,
8
h
AUC
0.84.
found
certain
variables
are
important
vary
depending
on
point
time
predict.
Efficient
monitoring
possible
by
utilizing
data
sensors
symptom
self-reports.
Review of Managerial Science,
Год журнала:
2023,
Номер
18(4), С. 1189 - 1220
Опубликована: Сен. 13, 2023
Abstract
The
introduction
of
ChatGPT
in
November
2022
by
OpenAI
has
stimulated
substantial
discourse
on
the
implementation
artificial
intelligence
(AI)
various
domains
such
as
academia,
business,
and
society
at
large.
Although
AI
been
utilized
numerous
areas
for
several
years,
emergence
generative
(GAI)
applications
ChatGPT,
Jasper,
or
DALL-E
are
considered
a
breakthrough
acceleration
technology
due
to
their
ease
use,
intuitive
interface,
performance.
With
GAI,
it
is
possible
create
variety
content
texts,
images,
audio,
code,
even
videos.
This
creates
implications
businesses
requiring
deeper
examination,
including
an
influence
business
model
innovation
(BMI).
Therefore,
this
study
provides
BMI
perspective
GAI
with
two
primary
contributions:
(1)
development
six
comprehensive
propositions
outlining
impact
businesses,
(2)
discussion
three
industry
examples,
specifically
software
engineering,
healthcare,
financial
services.
employs
qualitative
analysis
using
scoping
review
methodology,
drawing
from
wide-ranging
sample
513
data
points.
These
include
academic
publications,
company
reports,
public
information
press
releases,
news
articles,
interviews,
podcasts.
thus
contributes
growing
management
research
concerning
AI's
potential
offers
practical
insights
into
how
utilize
develop
new
improve
existing
models.
Nanoscale,
Год журнала:
2023,
Номер
15(18), С. 8044 - 8083
Опубликована: Янв. 1, 2023
Skin
patches
(SPs)
have
rapidly
advanced
to
rehabilitation,
health
monitoring,
self-powered
and
integrated
systems.
Accordingly,
design
of
nanomaterials,
flexible
substrates,
hydrogels
nanofibers
can
facilitate
the
therapeutic
application
SPs.
JMIR mhealth and uhealth,
Год журнала:
2024,
Номер
12, С. e56972 - e56972
Опубликована: Авг. 30, 2024
Wearable
activity
trackers,
including
fitness
bands
and
smartwatches,
offer
the
potential
for
disease
detection
by
monitoring
physiological
parameters.
However,
their
accuracy
as
specific
diagnostic
tools
remains
uncertain.
Abstract
Artificial
intelligence
(AI)
is
rapidly
advancing,
yet
its
applications
in
radiology
remain
relatively
nascent.
From
a
spatiotemporal
perspective,
this
review
examines
the
forces
driving
AI
development
and
integration
with
medicine
radiology,
particular
focus
on
advancements
addressing
major
diseases
that
significantly
threaten
human
health.
Temporally,
advent
of
foundational
model
architectures,
combined
underlying
drivers
development,
accelerating
progress
interventions
their
practical
applications.
Spatially,
discussion
explores
potential
evolving
methodologies
to
strengthen
interdisciplinary
within
medicine,
emphasizing
four
critical
points
imaging
process,
as
well
application
disease
management,
including
emergence
commercial
products.
Additionally,
current
utilization
deep
learning
reviewed,
future
through
multimodal
foundation
models
Generative
Pre‐trained
Transformer
are
anticipated.
ACS Applied Materials & Interfaces,
Год журнала:
2023,
Номер
15(24), С. 29486 - 29498
Опубликована: Июнь 9, 2023
The
increasing
prevalence
of
health
problems
stemming
from
sedentary
lifestyles
and
evolving
workplace
cultures
has
placed
a
substantial
burden
on
healthcare
systems.
Consequently,
remote
wearable
monitoring
systems
have
emerged
as
essential
tools
to
track
individuals'
well-being.
Self-powered
triboelectric
nanogenerators
(TENGs)
exhibited
significant
potential
for
use
emerging
detection
devices
capable
recognizing
body
movements
breathing
patterns.
However,
several
challenges
remain
be
addressed
in
order
fulfill
the
requirements
self-healing
ability,
air
permeability,
energy
harvesting,
suitable
sensing
materials.
These
materials
must
possess
high
flexibility,
lightweight,
excellent
charging
effects
both
electropositive
electronegative
layers.
In
this
work,
we
investigated
self-healable
electrospun
polybutadiene-based
urethane
(PBU)
positive
layer
titanium
carbide
(Ti3C2Tx)
MXene
negative
fabrication
an
energy-harvesting
TENG
device.
PBU
consists
maleimide
furfuryl
components
well
hydrogen
bonds
that
trigger
Diels–Alder
reaction,
contributing
its
properties.
Moreover,
incorporates
multitude
carbonyl
amine
groups,
which
create
dipole
moments
stiff
flexible
segments
polymer.
This
characteristic
positively
influences
qualities
by
facilitating
electron
transfer
between
contacting
materials,
ultimately
resulting
output
performance.
We
employed
device
applications
monitor
human
motion
pattern
recognition.
soft
fibrous-structured
generates
stable
open-circuit
voltage
up
30
V
short-circuit
current
4
μA
at
operation
frequency
4.0
Hz,
demonstrating
remarkable
cyclic
stability.
A
feature
our
is
allows
restoration
functionality
performance
after
sustaining
damage.
been
achieved
through
utilization
fibers,
can
repaired
via
simple
vapor
solvent
method.
innovative
approach
enables
maintain
optimal
continue
functioning
effectively
even
multiple
uses.
After
integration
with
rectifier,
charge
various
capacitors
power
120
LEDs.
self-powered
active
sensor,
attaching
it
purposes.
Additionally,
demonstrates
capability
recognize
patterns
real
time,
offering
valuable
insights
into
individual's
respiratory
health.
Immunosuppressed
patients,
particularly
those
with
cancer,
represent
a
momentous
and
increasing
portion
of
the
population,
especially
as
cancer
incidence
rises
population
growth
aging.
These
patients
are
at
heightened
risk
developing
severe
infections,
including
sepsis
septic
shock,
due
to
multiple
immunologic
defects
such
neutropenia,
lymphopenia,
T
B-cell
impairment.
The
diverse
complex
nature
these
profiles,
compounded
by
concomitant
use
immunosuppressive
therapies
(e.g.,
corticosteroids,
cytotoxic
drugs,
immunotherapy),
superimposed
breakage
natural
protective
barriers
mucosal
damage,
chronic
indwelling
catheters,
alterations
anatomical
structures),
increases
various
infections.
other
conditions
that
mimic
pose
substantial
diagnostic
therapeutic
challenges.
Factors
elevate
progression
shock
in
include
advanced
age,
pre-existing
comorbidities,
frailty,
type
severity
immunosuppression,
hypoalbuminemia,
hypophosphatemia,
Gram-negative
bacteremia,
timing
responses
initial
treatment.
management
vulnerable
or
varies
biased
clinical
practices
may
result
delayed
access
intensive
care
worse
outcomes.
While
is
typically
associated
poor
outcomes
malignancies,
survival
has
significantly
improved
over
time.
Therefore,
understanding
addressing
unique
needs
through
new
paradigm,
which
includes
integration
innovative
technologies
into
our
healthcare
system
wireless
technologies,
medical
informatics,
precision
medicine),
targeted
strategies,
robust
practices,
early
identification
diagnosis,
coupled
prompt
admission
high-level
facilities
promote
multidisciplinary
approach,
crucial
for
improving
their
prognosis
overall
rates.
Objective
This
review
aims
to
systematically
map
and
categorize
the
current
state
of
wearable
applications
among
oncology
patients
identify
determinants
impeding
clinical
implementation.
Methods
A
Medline,
Embase
clinicaltrials.gov
search
identified
journal
articles,
conference
abstracts,
letters,
reports,
dissertations
registered
studies
on
use
wearables
in
with
malignancies
published
up
10
November
2021.
Results
Of
2509
records
identified,
112
met
eligibility
criteria.
these,
9.8%
(11/112)
were
RCTs
47.3%
(53/112)
publications
observational.
Wearables
investigated
pre-treatment
(2.7%;
3/112),
during
treatment
(34.8%;
39/112),
post-treatment
(17.9%;
20/112),
survivors
(27.7%;
31/112)
non-specified
or
multiple
phases
(17.0%;
19/112).
Medical-grade
applied
22.3%
(25/112)
publications.
Primary
objectives
ranged
from
technical
feasibility
(8.0%;
9/112),
user
(42.9%;
48/112)
correlational
analysis
(40.2%;
45/112)
outcome
change
(8.9%;
10/112).
Outcome
was
mostly
regarding
physical
activity
improvement
(80.0%;
8/10).
Most
(39.3%;
24/61)
featured
cancer
types,
breast
as
most
prevalent
specific
type
(22.3%
publications,
16.4%
studies).
Conclusions
using
are
focused
assessing
consumer-grade
wearables,
whereas
rates
efficacy
low.
Substantial
improvements
clinically
relevant
endpoints
by
such
morbidity
mortality
yet
be
demonstrated.
