Non-enzymatic Colorimetric Glucose Detection Based on Au/Ag Nanoparticles Using Smartphone and Machine Learning-Reference-Cited by-同舟云学术

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Non-enzymatic Colorimetric Glucose Detection Based on Au/Ag Nanoparticles Using Smartphone and Machine Learning

Published:2021 Issue: Volume: Page:
ISSN:0910-6340
Container-title:Analytical Sciences
language:en
Short-container-title:Anal. Sci.

Author:

KILIÇ Volkan¹,MERCAN Öykü B.¹,TETIK Mehmet²,KAP Özlem³,HORZUM Nesrin³

Affiliation:

1. Department of Electrical and Electronics Engineering, Izmir Katip Celebi University

2. Department of Biocomposite Engineering, Graduate School of Natural and Applied Sciences, Izmir Katip Celebi University

3. Department of Engineering Sciences, İzmir Katip Çelebi University

Publisher

Springer Science and Business Media LLC

Subject

Analytical Chemistry

Link

https://www.jstage.jst.go.jp/article/analsci/advpub/0/advpub_21P253/_pdf

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1. Machine learning-assisted image-based optical devices for health monitoring and food safety;TrAC Trends in Analytical Chemistry;2024-08

2. Multilayered Fe3O4@(ZIF-8)3 combined with a computer-vision-enhanced immunosensor for chloramphenicol enrichment and detection;Journal of Hazardous Materials;2024-05

3. Colorimetric detection of glucose with smartphone-coupled µPADs: harnessing machine learning algorithms in variable lighting environments;Sensors and Actuators B: Chemical;2024-02

4. Unlocking the potential of bioanalytical data through machine learning;Analytical Sciences;2023-11-22

5. Predictive Framework Development for User-Friendly On-Site Glucose Detection;ACS Applied Bio Materials;2023-09-08

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