Deep Learning-Enhanced Paper-Based Vertical Flow Assay for High-Sensitivity Troponin Detection Using Nanoparticle Amplification

Deep Learning-Enhanced Paper-Based Vertical Flow Assay for High-Sensitivity Troponin Detection Using Nanoparticle Amplification

Successful integration of point-of-care testing (POCT) into clinical settings requires improved assay sensitivity and precision to match laboratory standards. Here, we show how innovations in amplified biosensing, imaging, and data processing, coupled with deep learning, can help improve POCT. To de...

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Bibliographic Details
Main Author: Gyeo-Re Han (8158410) (author)
Other Authors: Artem Goncharov (10103910) (author), Merve Eryilmaz (18846953) (author), Hyou-Arm Joung (2090581) (author), Rajesh Ghosh (7411787) (author), Geon Yim (19802847) (author), Nicole Chang (19802850) (author), Minsoo Kim (171626) (author), Kevin Ngo (19802853) (author), Marcell Veszpremi (19416101) (author), Kun Liao (396580) (author), Omai B. Garner (245658) (author), Dino Di Carlo (8063840) (author), Aydogan Ozcan (138135) (author)
Published: 2024
Subjects:
Medicine
Biotechnology
Space Science
Biological Sciences not elsewhere classified
Chemical Sciences not elsewhere classified
Information Systems not elsewhere classified
satisfying clinical requirements
large dynamic range
digital assay validation
biomarker widely used
benchtop clinical analyzer
assessing cardiovascular risk
covering ctni concentrations
match laboratory standards
help improve poct
based biomarker testing
based computational hs
ctni ),
based sensor
computational hs
computational algorithms
care testing
blinded testing
strong correlation
quantitative measurement
portable reader
patient samples
outlier detection
nanoparticle amplification
home test
enhanced paper
effective paper
effective alternative
detection limit
democratize access
deep learning
data processing
colorimetric paper
care diagnostics
cardiac troponin
based high
amplified biosensing
accurate quantification
6 orders
2 pg
100 ng
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