ArticleACS nano2023
Virus Detection and Identification in Minutes Using Single-Particle Imaging and Deep Learning.
Article in ACS nano, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Review
- Fluorescence encoding technology based tetrahedral nano-string for logic identification of breast cancer cells.Materials today. Bio · 2026Article
- Morphology-guided deep learning for nanoparticle agglomeration diagnostic assays.Scientific reports · 2026Article
- Overview in Machine-Learning-Assisted Sensing Techniques for Monitoring COVID-19.Micromachines · 2026Review
- Real-Time Fluorescence-Based COVID-19 Diagnosis Using a Lightweight Deep Learning System.Sensors (Basel, Switzerland) · 2026Article
- Atomic force microscopy-based topographical imaging of SARS-CoV-2 as part of a tripartite strategy for RNA virus characterization.Journal of translational medicine · 2025Article
- Enhanced testing can substantially improve defense against several types of respiratory virus pandemic.Epidemics · 2025Article
- Integrated Antigenic and Nucleic Acid Detection in Single Virions and Extracellular Vesicles with Viral Content.Advanced healthcare materials · 2025Article
- Article
- Significance of Artificial Intelligence in the Study of Virus-Host Cell Interactions.Biomolecules · 2024Review
- Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence.Microorganisms · 2024Review
- Article
- Rapid and specific detection of single nanoparticles and viruses in microfluidic laminar flow via confocal fluorescence microscopy.bioRxiv : the preprint server for biology · 2024Article
- Mosaic quadrivalent influenza vaccine single nanoparticle characterization.Scientific reports · 2024Article
- Tools and methods for high-throughput single-cell imaging with the mother machine.bioRxiv : the preprint server for biology · 2024Article
- Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles.Frontiers in immunology · 2024Article
- Article
- Solid-Phase Optical Sensing Techniques for Sensitive Virus Detection.Sensors (Basel, Switzerland) · 2023Review
- COVID-19 lateral flow test image classification using deep CNN and StyleGAN2.Frontiers in artificial intelligence · 2023Article
- Healthcare Innovations to Address the Challenges of the COVID-19 Pandemic.IEEE journal of biomedical and health informatics · 2022Article
Corrections and comments
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Authors and funding
16 authors.
Funding
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 related strains of influenza, as well as SARS-CoV-2 variants. Additional and novel pathogens can easily be incorporated into the test through software updates, offering the potential to rapidly utilize the technology in future infectious disease outbreaks or pandemics. Single-particle imaging combined with deep learning therefore offers a promising alternative to traditional viral diagnostic and genomic sequencing methods and has the potential for significant impact.
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