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A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine
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 COVI...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9755752/ https://www.ncbi.nlm.nih.gov/pubmed/36530356 http://dx.doi.org/10.3389/frai.2022.1034732 |
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author | Shen, John Ghatti, Siddharth Levkov, Nate Ryan Shen, Haiying Sen, Tanmoy Rheuban, Karen Enfield, Kyle Facteau, Nikki Reyer Engel, Gina Dowdell, Kim |
author_facet | Shen, John Ghatti, Siddharth Levkov, Nate Ryan Shen, Haiying Sen, Tanmoy Rheuban, Karen Enfield, Kyle Facteau, Nikki Reyer Engel, Gina Dowdell, Kim |
author_sort | Shen, John |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9755752 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97557522022-12-17 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 Front Artif Intell Artificial Intelligence 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. Frontiers Media S.A. 2022-12-02 /pmc/articles/PMC9755752/ /pubmed/36530356 http://dx.doi.org/10.3389/frai.2022.1034732 Text en Copyright © 2022 Shen, Ghatti, Levkov, Shen, Sen, Rheuban, Enfield, Facteau, Engel and Dowdell. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Artificial Intelligence Shen, John Ghatti, Siddharth Levkov, Nate Ryan Shen, Haiying Sen, Tanmoy Rheuban, Karen Enfield, Kyle Facteau, Nikki Reyer Engel, Gina Dowdell, Kim A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine |
title | A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine |
title_full | A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine |
title_fullStr | A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine |
title_full_unstemmed | A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine |
title_short | A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine |
title_sort | survey of covid-19 detection and prediction approaches using mobile devices, ai, and telemedicine |
topic | Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9755752/ https://www.ncbi.nlm.nih.gov/pubmed/36530356 http://dx.doi.org/10.3389/frai.2022.1034732 |
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