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Anal Chem ; 93(26): 9174-9182, 2021 07 06.
Artículo en Inglés | MEDLINE | ID: mdl-34155883

RESUMEN

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.


Asunto(s)
COVID-19 , Aprendizaje Profundo , Humanos , SARS-CoV-2 , Sensibilidad y Especificidad , Espectrometría Raman , Esputo
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