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Updated: Jun 29, 2025
Rapid Homogeneous Detection of Biological Assays Using Magnetic Modulation Biosensing System
Published on: June 13, 2010
Detection of SARS-CoV-2 using machine learning-enabled paper-assisted ratiometric fluorescent sensors based on
Wenhai Wang1, Lun Luo1, Yanmei Li1
1School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006, Guangdong Province, China.
Abstract:
The development of an advanced analytical platform with regard to SARS-CoV-2 is crucial for public health. Herein, we present a machine learning platform based on paper-assisted ratiometric fluorescent sensors for highly sensitive detection of the SARS-CoV-2 RdRp gene. The assay involves target-induced rolling circle amplification to generate magnetic DNAzyme, which is then detectable using the paper-assisted ratiometric fluorescent sensor. This sensor detects the SARS-CoV-2 RdRp gene with a visible-fluorescence color response. Moreover, leveraging different fluorescence responses, the ResNet algorithm of machine learning assists in accurately identifying fluorescence images and differentiating the concentration of the SARS-CoV-2 RdRp gene with over 99% recognition accuracy. The machine learning platform exhibits exceptional sensitivity and color responsiveness, achieving a limit of detection of 30 fM for the SARS-CoV-2 RdRp gene. The integration of intelligent artificial vision with the paper-assisted ratiometric fluorescent sensor presents a novel approach for the on-site detection of COVID-19 and holds potential for broader use in disease diagnostics in the future.
