Microfluidic paper-based analytical devices: from design to applications

E Noviana, T Ozer, CS Carrell, JS Link… - Chemical …, 2021 - ACS Publications
Microfluidic paper-based analytical devices (μPADs) have garnered significant interest as a
promising analytical platform in the past decade. Compared with traditional microfluidics …

Point-of-care testing based on smartphone: The current state-of-the-art (2017–2018)

J Liu, Z Geng, Z Fan, J Liu, H Chen - Biosensors and Bioelectronics, 2019 - Elsevier
Smartphone-based point-of-care testing (POCT) is rapidly emerging as a potential
alternative to the traditional laboratory-based diagnostic testing owing to economic …

Smartphone embedded deep learning approach for highly accurate and automated colorimetric lactate analysis in sweat

E Yüzer, V Doğan, V Kılıç, M Şen - Sensors and Actuators B: Chemical, 2022 - Elsevier
Here, a microfluidic paper-based analytical device (μPAD) was first combined with a deep
learning-based smartphone app called “DeepLactate” and then applied for quantitative and …

[HTML][HTML] Nanozyme-based colorimetric biosensor with a systemic quantification algorithm for noninvasive glucose monitoring

HJ Jeon, HS Kim, E Chung, DY Lee - Theranostics, 2022 - ncbi.nlm.nih.gov
Diabetes mellitus accompanies an abnormally high glucose level in the bloodstream. Early
diagnosis and proper glycemic management of blood glucose are essential to prevent …

Machine learning-based colorimetric determination of glucose in artificial saliva with different reagents using a smartphone coupled μPAD

ÖB Mercan, V Kılıç, M Şen - Sensors and Actuators B: Chemical, 2021 - Elsevier
Abstract Potassium iodide (KI) and 3, 3′, 5, 5′-tetramethylbenzidine (TMB) are frequently
used as chromogenic agents in μ PADs for glucose determination. Chitosan (Chi) has …

Big data and machine learning for materials science

JF Rodrigues, L Florea, MCF de Oliveira, D Diamond… - Discover …, 2021 - Springer
Herein, we review aspects of leading-edge research and innovation in materials science
that exploit big data and machine learning (ML), two computer science concepts that …

Smartphone-based colorimetric detection systems for glucose monitoring in the diagnosis and management of diabetes

Ö Kap, V Kılıç, JG Hardy, N Horzum - Analyst, 2021 - pubs.rsc.org
Diabetes is a group of metabolic conditions resulting in high blood sugar levels over
prolonged periods that affects hundreds of millions of patients worldwide. Measuring …

Machine learning enhances the performance of bioreceptor-free biosensors

KE Schackart III, JY Yoon - Sensors, 2021 - mdpi.com
Since their inception, biosensors have frequently employed simple regression models to
calculate analyte composition based on the biosensor's signal magnitude. Traditionally …

Colorimetric biosensor based on smartphone: State-of-art

Z Geng, Y Miao, G Zhang, X Liang - Sensors and Actuators A: Physical, 2023 - Elsevier
Smartphone-based colorimetric sensors can be operated out of the laboratory, meeting
urgent needs such as point-of-care testing and on-site diagnostics. The quality of the …

Quantifying colorimetric tests using a smartphone app based on machine learning classifiers

ME Solmaz, AY Mutlu, G Alankus, V Kılıç… - Sensors and Actuators B …, 2018 - Elsevier
A smartphone application based on machine learning classifier algorithms was developed
for quantifying peroxide content on colorimetric test strips. The strip images were taken from …