首页|Detection of SARS-CoV-2 based on artificial intelligence-assisted smartphone:A review

Detection of SARS-CoV-2 based on artificial intelligence-assisted smartphone:A review

扫码查看
原文链接
  • 万方数据
  • 维普
In recent years,the application of smartphone in various fields has received great attention,and it has become a promising tool in virus detection,data processing and data exchange.During the rapid spread of COVID-19 around the world,many traditional detection methods have been combined with smart-phone to assist in the analysis and detection of the novel coronavirus(SARS-CoV-2),including electro-chemistry,fluorescence and colorimetry.With the gradual development of artificial intelligence(AI),the combination of AI and smartphone to analyze SARS-CoV-2 was also the focus of research.Based on the summary of the traditional methods combined with smartphone to detect SARS-CoV-2 virus,in addition to AI-based data processing,AI algorithms are also employed for SARS-CoV-2 detection itself.This review discussed both strategies and focused on the application of the former.The combination of AI algorithm and smartphone to detect SARS-CoV-2 has high accuracy,which is more conducive to meeting the needs of portable detection.In addition,the classification of SARS-CoV-2 virus samples in biological fluids such as blood and saliva was also discussed.Finally,this paper briefly discussed the limitations of using smart-phone analysis to detect SARS-CoV-2,as well as the prospect and future development of virus detection.In conclusion,the detection methods based on smartphone and AI algorithms show great potential in the detection of SARS-CoV-2 and can be a valuable complement to traditional analysis methods.

COVID-19SARS-CoV-2 virusDetection methodSmartphone analysisArtificial intelligence

Yunxin Li、Jinghui Zhang、Jisen Chen、Feng Zhu、Zhiqiang Liu、Peng Bao、Wei Shen、Sheng Tang

展开 >

School of Environmental and Chemical Engineering,Jiangsu University of Science and Technology,Zhenjiang 212003,China

Programme in Emerging Infectious Diseases,Duke-NUS Medical School,Singapore 169857,Singapore

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNatural Science Foundation of Jiangsu Province,ChinaNatural Science Foundation of Jiangsu Province,China

216051052220406422276080BK20211340BK20220645

2024

10.1016/j.cclet.2023.109220

中国化学快报(英文版)
中国化学会

中国化学快报(英文版)

CSTPCD
影响因子：0.771
ISSN：1001-8417
年,卷(期)：2024.35(7)