首页    期刊浏览 2024年10月06日 星期日
登录注册

文章基本信息

  • 标题:Applying Machine Learning with Localized Surface Plasmon Resonance Sensors to Detect SARS-CoV-2 Particles
  • 本地全文:下载
  • 作者:Jiawei Liang ; Wei Zhang ; Yu Qin
  • 期刊名称:Biosensors
  • 电子版ISSN:2079-6374
  • 出版年度:2022
  • 卷号:12
  • 期号:3
  • DOI:10.3390/bios12030173
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:The sudden outbreak of COVID-19 rapidly developed into a global pandemic, which caused tens of millions of infections and millions of deaths. Although SARS-CoV-2 is known to cause COVID-19, effective approaches to detect SARS-CoV-2 using a convenient, rapid, accurate, and low-cost method are lacking. To date, most of the diagnostic methods for patients with early infections are limited to the detection of viral nucleic acids via polymerase chain reaction (PCR), or antigens, using an enzyme-linked immunosorbent assay or a chemiluminescence immunoassay. This study developed a novel method that uses localized surface plasmon resonance (LSPR) sensors, optical imaging, and artificial intelligence methods to directly detect the SARS-CoV-2 virus particles without any sample preparation. The virus concentration can be qualitatively and quantitatively detected in the range of 125.28 to 10 6 vp/mL through a few steps within 12 min with a limit of detection (LOD) of 100 vp/mL. The accuracy of the SARS-CoV-2 positive or negative assessment was found to be greater than 97%, and this was demonstrated by establishing a regression machine learning model for the virus concentration prediction (R 2 > 0.95).
  • 关键词:enSARS-CoV-2machine learningLSPR sensormicroscopic imaging
国家哲学社会科学文献中心版权所有