Virus Detection and Identification in Minutes Using Single-Particle Imaging and Deep Learning.

ABSTRACT: The increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive diagnostic methods. Here, we present a methodology for virus detection and identification that uses a convolutional neural network to distinguish between microscopy images of fluorescently labeled intact particles of different viruses. Our assay achieves labeling, imaging, and virus identification in less than 5 min and does not require any lysis, purification, or amplification steps. The trained neural network was able to differentiate SARS-CoV-2 from negative clinical samples, as well as from other common respiratory pathogens such as influenza and seasonal human coronaviruses. We were also able to differentiate closely r

SUBMITTER: Shiaelis N 

PROVIDER: S-EPMC9836350 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature