On-Site Detection of SARS-CoV-2 Antigen by Deep Learning-Based Surface-Enhanced Raman Spectroscopy and Its Biochemical Foundations.
Anal Chem
; 93(26): 9174-9182, 2021 07 06.
Article
in English
| MEDLINE | ID: covidwho-1279803
ABSTRACT
A rapid, on-site, and accurate SARS-CoV-2 detection method is crucial for the prevention and control of the COVID-19 epidemic. However, such an ideal screening technology has not yet been developed for the diagnosis of SARS-CoV-2. Here, we have developed a deep learning-based surface-enhanced Raman spectroscopy technique for the sensitive, rapid, and on-site detection of the SARS-CoV-2 antigen in the throat swabs or sputum from 30 confirmed COVID-19 patients. A Raman database based on the spike protein of SARS-CoV-2 was established from experiments and theoretical calculations. The corresponding biochemical foundation for this method is also discussed. The deep learning model could predict the SARS-CoV-2 antigen with an identification accuracy of 87.7%. These results suggested that this method has great potential for the diagnosis, monitoring, and control of SARS-CoV-2 worldwide.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Deep Learning
/
COVID-19
Type of study:
Diagnostic study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
Anal Chem
Year:
2021
Document Type:
Article
Affiliation country:
Acs.analchem.1c01061
Similar
MEDLINE
...
LILACS
LIS