Rapid Parallel Search Technology with Scanning Electron Microscope and Artificial Neural Network

被引:0
|
作者
Shulunov, Vyacheslav R. [1 ]
机构
[1] Russian Acad Sci, Inst Phys Mat Sci, Siberian Branch, Sakhyanovoi St 6, Ulan Ude 670047, Russia
关键词
SARS-CoV-2; COVID-19; scanning electron microscopy; automated virus detection; computer-aided diagnosis; automated image analysis; SARS CORONAVIRUS; INFECTION; TESTS;
D O I
10.1080/23080477.2022.2092671
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
It is shown how to prevent and monitor the spread of any respiratory viral outbreaks by precisely and quickly identifying patients and asymptomatic carriers by nano technology. Rapid Parallel Search (RPS) derived from a combination of time-proved methods, hardware and software components such as Scanning Electron Microscopy (SEM), Artificial Neural Network (ANN) and a recognition system similar to 'Face ID' from 'Apple Inc.'. High performance and classification precision (similar to 50 s per test with 99.999% accuracy) for detecting the presence of all known viruses and microorganisms, that are hard or impossible to identify with molecular methods, are achieved through simultaneous automatic testing of hundreds of samples with scanning resolution of 0.5 nm. RPS has sufficient potential for real-time monitoring of all passengers of huge transcontinental airports and daily, precisely supervising of the vast majority of residents of a city with a population of one million or more without reagents.
引用
收藏
页码:364 / 370
页数:7
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