Detection Methods of COVID-19

被引:0
|
作者
Echtioui, Amira [1 ]
Zouch, Wassim [2 ]
Ghorbel, Mohamed [1 ]
Mhiri, Chokri [3 ,4 ]
Hamam, Habib [5 ]
机构
[1] Univ Sfax, ATMS Lab, Adv Technol Med & Signals, ENIS, Sfax 3038, Tunisia
[2] King Abdulaziz Univ KAU, Jeddah, Saudi Arabia
[3] Habib Bourguiba Univ Hosp, Dept Neurol, Sfax, Tunisia
[4] Sfax Univ, Fac Med, Neurosci Lab LR 12 SP 19, Sfax, Tunisia
[5] Moncton Univ, Fac Engn, Moncton, NB, Canada
来源
SLAS TECHNOLOGY | 2020年 / 25卷 / 06期
关键词
COVID-19; convolutional neural network; CNN; deep learning; diagnosis; IMAGES;
D O I
10.1177/2472630320962002
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Since being first detected in China, coronavirus disease 2019 (COVID-19) has spread rapidly across the world, triggering a global pandemic with no viable cure in sight. As a result, national responses have focused on the effective minimization of the spread. Border control measures and travel restrictions have been implemented in a number of countries to limit the import and export of the virus. The detection of COVID-19 is a key task for physicians. The erroneous results of early laboratory tests and their delays led researchers to focus on different options. Information obtained from computed tomography (CT) and radiological images is important for clinical diagnosis. Therefore, it is worth developing a rapid method of detection of viral diseases through the analysis of radiographic images. We propose a novel method of detection of COVID-19. The purpose is to provide clinical decision support to healthcare workers and researchers. The article is to support researchers working on early detection of COVID-19 as well as similar viral diseases.
引用
收藏
页码:566 / 572
页数:7
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