A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

被引：4

作者：

Shen, John ^{[1
]}

Ghatti, Siddharth ^{[1
]}

Levkov, Nate Ryan ^{[1
]}

Shen, Haiying ^{[1
]}

Sen, Tanmoy ^{[1
]}

Rheuban, Karen ^{[2
]}

Enfield, Kyle ^{[2
]}

Facteau, Nikki Reyer ^{[3
]}

Engel, Gina ^{[2
]}

Dowdell, Kim ^{[2
]}

机构：

[1] Univ Virginia, Dept Comp Sci, Charlottesville, VA 22904 USA

[2] Univ Virginia, Sch Med, Charlottesville, VA USA

[3] Univ Virginia, Univ Virginia UVA Hlth Syst, Charlottesville, VA USA

来源：

FRONTIERS IN ARTIFICIAL INTELLIGENCE | 2022年 / 5卷

关键词：

COVID-19; detection; mobile devices; AI; telemedicine; IoT; ARTIFICIAL-INTELLIGENCE; HEALTH-CARE; SYSTEM; IOT; SURVEILLANCE; FRAMEWORK; INTERNET; THINGS; 5G;

D O I：

10.3389/frai.2022.1034732

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Since 2019, the COVID-19 pandemic has had an extremely high impact on all facets of the society and will potentially have an everlasting impact for years to come. In response to this, over the past years, there have been a significant number of research efforts on exploring approaches to combat COVID-19. In this paper, we present a survey of the current research efforts on using mobile Internet of Thing (IoT) devices, Artificial Intelligence (AI), and telemedicine for COVID-19 detection and prediction. We first present the background and then present current research in this field. Specifically, we present the research on COVID-19 monitoring and detection, contact tracing, machine learning based approaches, telemedicine, and security. We finally discuss the challenges and the future work that lay ahead in this field before concluding this paper.

引用

页数：15

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