Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Mais filtros

Base de dados
Ano de publicação
Tipo de documento
País de afiliação
Intervalo de ano de publicação
1.
Biosensors (Basel) ; 12(12)2022 Nov 23.
Artigo em Inglês | MEDLINE | ID: mdl-36551032

RESUMO

We demonstrate the possibility of applying surface-enhanced Raman spectroscopy (SERS) combined with machine learning technology to detect and differentiate influenza type A and B viruses in a buffer environment. The SERS spectra of the influenza viruses do not possess specific peaks that allow for their straight classification and detection. Machine learning technologies (particularly, the support vector machine method) enabled the differentiation of samples containing influenza A and B viruses using SERS with an accuracy of 93% at a concentration of 200 µg/mL. The minimum detectable concentration of the virus in the sample using the proposed approach was ~0.05 µg/mL of protein (according to the Lowry protein assay), and the detection accuracy of a sample with this pathogen concentration was 84%.


Assuntos
Herpesvirus Cercopitecino 1 , Vírus da Influenza A , Influenza Humana , Orthomyxoviridae , Humanos , Análise Espectral Raman/métodos , Influenza Humana/diagnóstico
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA