Pharmaceuticals,
Год журнала:
2023,
Номер
16(7), С. 1042 - 1042
Опубликована: Июль 22, 2023
Background
and
rationale.
The
therapeutic
interventions
against
lung
cancer
are
currently
based
on
a
fully
personalized
approach
to
the
disease
with
considerable
improvement
of
patients’
outcome.
Alongside
continuous
scientific
progresses
research
investments,
massive
technologic
efforts,
innovative
challenges,
consolidated
achievements
together
investments
at
bases
engineering
manufacturing
revolution
that
allows
significant
gain
in
clinical
setting.
Aim
methods.
scope
this
review
is
thus
focus,
rather
than
biologic
traits,
analysis
precision
sensors
novel
generation
materials,
as
semiconductors,
which
below
development
diagnosis
treatment.
In
perspective,
careful
revision
state
art
literature
experimental
knowledge
presented.
Results.
Novel
materials
being
used
treatment
for
cancer.
Among
them,
semiconductors
analyze
volatile
compounds
allow
early
diagnosis.
Moreover,
they
can
be
generate
MEMS
have
found
an
application
advanced
imaging
techniques
well
drug
delivery
devices.
Conclusions.
Overall,
these
issues
represent
critical
only
partially
known
generally
underestimated
by
community.
These
micro-technology-based
biosensing
devices,
use
molecules
atomic
concentrations,
crucial
innovation
since
allowed
recent
advances
biology
deciphering
detection
therapy.
There
urgent
need
create
stronger
dialogue
between
technologists,
basic
researchers,
clinicians
address
all
efforts
towards
real
Here,
great
attention
focused
their
cancer,
from
exploitations
translational
development,
ensure
better
outcomes.
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Фев. 19, 2025
Skin
diseases,
a
significant
category
in
the
medical
field,
have
always
been
challenging
to
diagnose
and
high
misdiagnosis
rate.
Deep
learning
for
skin
disease
classification
has
considerable
value
clinical
diagnosis
treatment.
This
study
proposes
model
based
on
multi-scale
channel
attention.
The
network
architecture
of
consists
three
main
parts:
an
input
module,
four
processing
blocks,
output
module.
Firstly,
improved
pyramid
segmentation
attention
module
extract
features
image
entirely.
Secondly,
reverse
residual
structure
is
used
replace
backbone
network,
integrated
into
achieve
better
feature
extraction.
Finally,
adaptive
average
pool
fully
connected
layer,
which
convert
aggregated
global
several
categories
generate
final
task.
To
verify
performance
proposed
model,
this
two
commonly
datasets,
ISIC2019
HAM10000,
validation.
experimental
results
showed
that
accuracy
was
77.6
$$\%$$
series
dataset
88.2
HAM10000
dataset.
External
validation
data
added
evaluation
validate
further,
comprehensive
proved
effectiveness
paper.
Healthcare
has
undergone
a
revolutionary
shift
with
the
advent
of
smart
technologies,
and
toilets
(STs)
are
among
innovative
inventions
offering
non-invasive
continuous
health
monitoring.
The
present
technical
challenges
toward
this
development
include
limited
sensitivity
integrated
sensors,
poor
stability,
slow
response
requirement
external
energy
supply
alongside
manual
sample
collection.
In
article,
triboelectric
nanosensor
array
(TENSA)
is
introduced
featuring
electrodes
crafted
from
laser-induced
3D
graphene
functional
polymers
like
polystyrene,
polyimide,
polycaprolactone
for
real-time
urine
analysis
while
generating
50
volts
output
via
droplet-based
triboelectrification.
Though
modulating
interfacial
double-layer
capacitance,
these
sensors
exhibit
exceptional
selectivity
in
detecting
broad
spectrum
urinary
biomarkers,
including
ions,
glucose,
urea
classification
precision
95%
concentration
identification
accuracy
up
to
0.97
(R
Communications Materials,
Год журнала:
2024,
Номер
5(1)
Опубликована: Июль 24, 2024
Abstract
Wearable
enzyme-based
biosensors
enable
advanced
healthcare
diagnostics
through
the
monitoring
of
biomarkers
and
physiological
states.
The
integration
materials
engineering
enzyme
conjugation
has
established
groundwork
for
advancements
in
modern
analytical
chemistry,
poised
to
extend
frontiers
wearable
biosensing
further.
Recent
enzymatic
biofuel
cells
have
also
enhanced
devices
by
harnessing
biofuels,
such
as
glucose
lactate
biofluids.
Importantly,
offer
potential
self-powered
biosensors.
Here,
we
present
an
overview
principles
considerations
associated
with
integrating
enzymes
electrodes
achieve
effective
self-sustaining
cell-based
energy
systems.
Furthermore,
discuss
challenges
encountered
sensors
cells.
Representative
applications
settings
are
highlighted,
along
a
summary
real
sample
analyses,
emphasizing
concentration
ranges
analytes
actual
sweat
samples
underscore
their
relevance
real-world
scenarios.
Finally,
discussion
explores
anticipated
impact
future
material
innovations
integrations
on
development
next-generation
biodevices.
This
Review
examines
the
potential
of
breathomics
in
enhancing
disease
monitoring
and
diagnostic
precision
when
integrated
with
artificial
intelligence
(AI)
electrochemical
sensing
techniques.
It
discusses
breathomics'
for
early
noninvasive
diagnosis
a
focus
on
chronic
kidney
(CKD),
obstructive
pulmonary
(COPD),
lung
cancer,
which
have
been
well
studied
context
VOC
association
diseases.
The
nature
exhaled
breath
analysis
can
be
advantageous
compared
to
traditional
methods
CKD,
often
rely
blood
urine
testing.
enhance
spirometry
imaging
used
COPD
diagnosis,
providing
more
comprehensive
picture
disease's
progression.
Breathomics
could
also
provide
less
intrusive
potentially
earlier
approach
is
now
dependent
biopsy.
combination
breathomics,
sensing,
AI
lead
personalized
successful
treatment
plans
illnesses
using
algorithms
decipher
complicated
patterns.
assesses
viability
effectiveness
combining
sensors
by
synthesizing
recent
research
findings
technological
developments.
International Journal of Medical Informatics,
Год журнала:
2025,
Номер
unknown, С. 105878 - 105878
Опубликована: Март 1, 2025
Falls
and
pressure
ulcers
are
serious
complications
impacting
care
quality
in
nursing
homes.
Sensor
technologies
can
help
prevent
these
adverse
events
through
continuous
monitoring
timely
intervention.
This
scoping
review,
following
JBI
guidelines,
evaluated
the
effects
of
sensor-based
fall
ulcer
prevention
long-term
experiences
patients
healthcare
professionals.
The
review
included
primary
studies,
reviews,
protocols
published
from
2014
to
2023.
Screening,
data
extraction,
appraisal
were
conducted
independently
by
two
authors
using
MMAT
tools.
A
total
31
studies
included:
22
on
prevention,
eight
one
addressing
both.
User-based
sensors
effective
preventing
both
falls
ulcers.
Accelerometers
enhanced
sensitivity
for
detection
adherence
repositioning
protocols.
Context-based
sensors,
such
as
Doppler,
webcams,
Kinect,
showed
variable
precision
false
alarm
rates,
while
range
demonstrated
high
precision.
accelerometers
promising
but
provided
inconsistent
data.
Additional
manual
assessments
sensor
accuracy.
Patients
preferred
non-obtrusive,
user-friendly
professionals
emphasized
need
seamless
integration
into
routines.
Both
groups
valued
real-time
alert
capabilities,
though
privacy
security
remained
concerns.
show
potential
enhancing
patient
safety
care,
further
refinement
is
needed
context-based
prevention.
Integrating
with
standard
improve
outcomes,
ethical
issues
essential
broader
acceptance.
Advances in computational intelligence and robotics book series,
Год журнала:
2025,
Номер
unknown, С. 69 - 106
Опубликована: Март 28, 2025
Digital
twins
and
medical
wearables
are
revolutionizing
healthcare
by
enabling
personalized,
real-time
monitoring
predictive
insights.
twins,
virtual
replicas
of
patients,
integrate
data
from
to
simulate
health
conditions,
predict
outcomes,
optimize
treatments.
Medical
such
as
smartwatches,
biosensors,
fitness
trackers
collect
continuous
data,
providing
insights
into
vital
signs,
activity
levels,
chronic
disease
management.
Together,
they
enhance
remote
patient
monitoring,
support
AI-driven
diagnostics,
facilitate
early
detection
anomalies.
This
synergy
accelerates
precision
medicine,
improves
empowers
proactive
healthcare,
marking
a
transformative
leap
in
innovation.
