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A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine.
Shen, John; Ghatti, Siddharth; Levkov, Nate Ryan; Shen, Haiying; Sen, Tanmoy; Rheuban, Karen; Enfield, Kyle; Facteau, Nikki Reyer; Engel, Gina; Dowdell, Kim.
  • Shen J; Department of Computer Science, University of Virginia, Charlottesville, VA, United States.
  • Ghatti S; Department of Computer Science, University of Virginia, Charlottesville, VA, United States.
  • Levkov NR; Department of Computer Science, University of Virginia, Charlottesville, VA, United States.
  • Shen H; Department of Computer Science, University of Virginia, Charlottesville, VA, United States.
  • Sen T; Department of Computer Science, University of Virginia, Charlottesville, VA, United States.
  • Rheuban K; School of Medicine, University of Virginia, Charlottesville, VA, United States.
  • Enfield K; School of Medicine, University of Virginia, Charlottesville, VA, United States.
  • Facteau NR; University of Virginia (UVA) Health System, University of Virginia, Charlottesville, VA, United States.
  • Engel G; School of Medicine, University of Virginia, Charlottesville, VA, United States.
  • Dowdell K; School of Medicine, University of Virginia, Charlottesville, VA, United States.
Front Artif Intell ; 5: 1034732, 2022.
Article in English | MEDLINE | ID: covidwho-2199578
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: Front Artif Intell Year: 2022 Document Type: Article Affiliation country: Frai.2022.1034732

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: Front Artif Intell Year: 2022 Document Type: Article Affiliation country: Frai.2022.1034732