Heliyon,
Journal Year:
2024,
Volume and Issue:
11(1), P. e41338 - e41338
Published: Dec. 18, 2024
AI-optimized
electrochemical
aptasensors
are
transforming
diagnostic
testing
by
offering
high
sensitivity,
selectivity,
and
rapid
response
times.
Leveraging
data-driven
AI
techniques,
these
sensors
provide
a
non-invasive,
cost-effective
alternative
to
traditional
methods,
with
applications
in
detecting
molecular
biomarkers
for
neurodegenerative
diseases,
cancer,
coronavirus.
The
performance
metrics
outlined
the
comparative
table
illustrate
significant
advancements
enabled
integration.
Sensitivity
increases
from
60
75
%
ordinary
85-95
%,
while
specificity
improves
70-80
90-98
%.
This
enhanced
allows
ultra-low
detection
limits,
such
as
10
fM
carcinoembryonic
antigen
(CEA)
20
mucin-1
(MUC1)
using
Electrochemical
Impedance
Spectroscopy
(EIS),
1
pM
prostate-specific
(PSA)
Differential
Pulse
Voltammetry
(DPV).
Similarly,
Square
Wave
(SWV)
potentiometric
have
detected
alpha-fetoprotein
(AFP)
at
5
epithelial
cell
adhesion
molecule
(EpCAM)
100
fM,
respectively.
integration
also
enhances
reproducibility,
reduces
false
positives
negatives
(from
15-20
5-10
%),
significantly
decreases
times
10-15
s
2-3
s).
These
improve
data
processing
speeds
min
per
sample
2-5
min)
calibration
accuracy
(<2
margin
of
error
compared
expanding
application
scope
multi-target
biomarker
detection.
review
highlights
how
position
powerful
tools
personalized
treatment,
point-of-care
testing,
continuous
health
monitoring.
Despite
higher
cost
($500-$1,500/unit),
their
portability
promise
revolutionize
healthcare,
environmental
monitoring,
food
safety,
ultimately
improving
public
outcomes.
Frontiers in Medicine,
Journal Year:
2025,
Volume and Issue:
12
Published: April 8, 2025
Modern
healthcare
depends
fundamentally
on
clinical
biochemistry
for
disease
diagnosis
and
therapeutic
guidance.
The
discipline
encounters
operational
constraints,
including
sampling
inefficiencies,
precision
limitations,
expansion
difficulties.
Recent
advancements
in
established
technologies,
such
as
mass
spectrometry
the
development
of
high-throughput
screening
point-of-care
are
revolutionizing
industry.
biosensor
technology
wearable
monitors
facilitate
continuous
health
tracking,
Artificial
Intelligence
(AI)/machine
learning
(ML)
applications
enhance
analytical
capabilities,
generating
predictive
insights
individualized
treatment
protocols.
However,
concerns
regarding
algorithmic
bias,
data
privacy,
lack
transparency
decision-making
("black
box"
models),
over-reliance
automated
systems
pose
significant
challenges
that
must
be
addressed
responsible
AI
integration.
limitations
remain-substantial
implementation
expenses,
system
incompatibility
issues,
information
security
vulnerabilities
intersect
with
ethical
considerations
fairness
protected
information.
Addressing
these
demands
coordinated
efforts
between
clinicians,
scientists,
technical
specialists.
This
review
discusses
current
biochemistry,
explicitly
addressing
reference
intervals
barriers
to
implementing
innovative
biomarkers
medical
settings.
discussion
evaluates
how
advanced
technologies
multidisciplinary
collaboration
can
overcome
constraints
while
identifying
research
priorities
diagnostic
accessibility
better
delivery.
Diagnostics,
Journal Year:
2025,
Volume and Issue:
15(8), P. 1037 - 1037
Published: April 18, 2025
Medical
biosensors
have
set
the
basis
of
medical
diagnostics,
and
Artificial
Intelligence
(AI)
has
boosted
diagnostics
to
a
great
extent.
However,
false
results
are
evident
in
every
method,
so
it
is
crucial
identify
reasons
behind
possible
result
order
control
its
occurrence.
This
first
critical
state-of-the-art
review
article
discuss
all
commonly
used
biosensor
types
that
can
give
rise
potential
results.
Furthermore,
AI
discussed
parallel
with
their
misdiagnoses,
again
some
for
discussed.
Finally,
an
expert
opinion
further
future
perspectives
presented
based
on
general
insights,
diagnostic
be
surpassed.
Research Square (Research Square),
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 23, 2025
Abstract
Healthcare
is
plagued
with
many
problems
that
Artificial
Intelligence
(AI)
can
ameliorate
or
sometimes
amplify.
Regardless,
AI
changing
the
way
we
reason
towards
solutions,
especially
at
frontier
of
public
health
applications
where
autonomous
and
co-pilot
integrated
systems
are
now
rapidly
adopted
for
mainstream
use
in
both
clinical
non-clinical
settings.
In
this
regard,
present
empirical
analysis
thematic
concerns
affect
patients
within
healthcare
how
experience
care
may
be
influenced
by
degree
integration.
Furthermore,
a
fairly
rigorous
mathematical
model
adopt
prevailing
techniques
Machine
Learning
(ML)
to
develop
models
utilize
patient's
general
information
responses
survey
predict
integration
will
maximize
their
care.
We
as
continuous
random
variable
on
open
interval
(-1,
1)
refer
it
AI
Affinity
Score
which
encapsulates
patient
prefers
chosen
system.
descriptive
statistics
distribution
over
key
demographic
variables
viz.
Age,
Gender,
Level
Education
well
summary
perceived
attitudes
these
categories.
further
results
statistical
tests
conducted
determine
if
variance
across
distributions
Scores
identified
groups
statistically
significant
access
behavior
any
independent
using
Bayesian
nonparametric
model.
Micromachines,
Journal Year:
2025,
Volume and Issue:
16(5), P. 522 - 522
Published: April 28, 2025
Wearable
and
implantable
BioMEMSs
(biomedical
microelectromechanical
systems)
have
transformed
modern
healthcare
by
enabling
continuous,
personalized,
minimally
invasive
monitoring,
diagnostics,
therapy.
advanced
rapidly,
encompassing
a
diverse
range
of
biosensors,
bioelectronic
systems,
drug
delivery
platforms,
motion
tracking
technologies.
These
devices
enable
non-invasive,
real-time
monitoring
biochemical,
electrophysiological,
biomechanical
signals,
offering
personalized
proactive
solutions.
In
parallel,
BioMEMS
significantly
enhanced
long-term
targeted
delivery,
neurostimulation.
From
continuous
glucose
intraocular
pressure
to
programmable
bioelectric
implants
for
neuromodulation,
these
are
improving
precision
treatment
localized
This
review
explores
the
materials
technologies
driving
advancements
in
wearable
BioMEMSs,
focusing
on
their
impact
chronic
disease
management,
cardiology,
respiratory
care,
glaucoma
treatment.
We
also
highlight
integration
with
artificial
intelligence
(AI)
Internet
Things
(IoT),
paving
way
smarter,
data-driven
Despite
potential,
face
challenges
such
as
regulatory
complexities,
global
standardization,
societal
determinants.
Looking
ahead,
we
explore
emerging
directions
like
multifunctional
biodegradable
power
sources,
next-generation
point-of-care
diagnostics.
Collectively,
position
pivotal
enablers
future
patient-centric
systems.
Deleted Journal,
Journal Year:
2025,
Volume and Issue:
2(1)
Published: May 2, 2025
Neurodegenerative
diseases
involve
the
progressive
loss
of
neurons
in
brain
and
nervous
system,
leading
to
functional
decline.
Early
detection
is
critical
for
improving
outcomes
advancing
therapies.
Optical
biosensors,
some
which
offer
rapid,
label-free,
ultra-sensitive
detection,
have
been
applied
early
diagnosis
drug
screening.
This
review
examines
principles
performance
different
optical
biosensors
used
diagnosing
neurodegenerative
discusses
potential
future
advancements.
