Rapid Detection of SARS-CoV-2 Variants Using an Angiotensin-Converting Enzyme 2-Based Surface-Enhanced Raman Spectroscopy Sensor Enhanced by CoVari Deep Learning Algorithms-Reference-Cited by-同舟云学术

Rapid Detection of SARS-CoV-2 Variants Using an Angiotensin-Converting Enzyme 2-Based Surface-Enhanced Raman Spectroscopy Sensor Enhanced by CoVari Deep Learning Algorithms

Published:2024-06-06 Issue:6 Volume:9 Page:3158-3169
ISSN:2379-3694
Container-title:ACS Sensors
language:en
Short-container-title:ACS Sens.

Author:

Yang Yanjun¹^ORCID,Cui Jiaheng²,Luo Dan³,Murray Jackelyn⁴,Chen Xianyan⁵,Hülck Sebastian⁶,Tripp Ralph A.⁴,Zhao Yiping¹^ORCID

Affiliation:

1. Department of Physics and Astronomy, The University of Georgia, Athens, Georgia 30602, United States

2. School of Electrical and Computer Engineering, College of Engineering, The University of Georgia, Athens, Georgia 30602, United States

3. Department of Statistics, The University of Georgia, Athens, Georgia 30602, United States

4. Department of Infectious Diseases, College of Veterinary Medicine, The University of Georgia, Athens, Georgia 30602, United States

5. Department of Epidemiology & Biostatistics, College of Public Health, The University of Georgia, Athens, Georgia 30602, United States

6. Tec5USA Inc., Plainview, New York 11803, United States

Funder

National Institute of Food and Agriculture

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acssensors.4c00488

Reference41 articles.

1. Optical technologies for the detection of viruses like COVID-19: Progress and prospects

2. Single Molecule Detection Using Surface-Enhanced Raman Scattering (SERS)

3. Probing Single Molecules and Single Nanoparticles by Surface-Enhanced Raman Scattering

4. Rapid and quantitative detection of respiratory viruses using surface-enhanced Raman spectroscopy and machine learning

5. Label-Free Spectroscopic SARS-CoV-2 Detection on Versatile Nanoimprinted Substrates

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