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.
International Journal of Molecular Sciences,
Journal Year:
2025,
Volume and Issue:
26(11), P. 5001 - 5001
Published: May 22, 2025
This
review
provides
a
comprehensive
overview
of
the
recent
advancements
in
nanosensors
and
microsensors
for
body
fluid
monitoring.
The
principles
behind
sensor
technologies,
their
applications
healthcare,
types
fluids
that
they
analyze
are
described
scope
this
paper.
Additionally,
discusses
emerging
trends,
challenges,
future
perspectives
field.
first
two
sections
explore
various
diagnostic
significance
discuss
fundamentals
classification
microsensors.
main
aim
paper
is
to
highlight
monitoring
examine
role
healthcare
diagnostics.
Innovative
solutions
such
as
microfluidic-based
sensors,
lab-on-a-chip
systems,
MEMS-based
wearable
implantable
sensors
discussed
section.
Various
construction
have
also
been
compiled
compared
based
on
target
analytes,
which
widely
present
fluids.
following
technologies
including
AI
integration
flexible
challenges
development
application
sensors.
conclusion
includes
summary
key
findings
outlook
personalized
medicine.
Frontiers in Chemistry,
Journal Year:
2024,
Volume and Issue:
12
Published: Oct. 17, 2024
Nanozymes,
synthetic
nanomaterials
that
mimic
the
catalytic
functions
of
natural
enzymes,
have
emerged
as
transformative
technologies
for
biosensing,
diagnostics,
and
environmental
monitoring.
Since
their
introduction,
nanozymes
rapidly
evolved
with
significant
advancements
in
design
applications,
particularly
through
integration
machine
learning
(ML).
Machine
(ML)
has
optimized
nanozyme
efficiency
by
predicting
ideal
size,
shape,
surface
chemistry,
reducing
experimental
time
resources.
This
review
explores
rapid
technology,
highlighting
role
ML
improving
performance
across
various
bioapplications,
including
real-time
monitoring
development
chemiluminescent,
electrochemical
colorimetric
sensors.
We
discuss
evolution
different
types
nanozymes,
mechanisms,
impact
on
property
optimization.
Furthermore,
this
addresses
challenges
related
to
data
quality,
scalability,
standardization,
while
future
directions
ML-driven
development.
By
examining
recent
innovations,
highlights
potential
combining
drive
next-generation
diagnostic
detection
technologies.
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.
