A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine.
AI
COVID-19 detection
IoT
mobile devices
telemedicine
Journal
Frontiers in artificial intelligence
ISSN: 2624-8212
Titre abrégé: Front Artif Intell
Pays: Switzerland
ID NLM: 101770551
Informations de publication
Date de publication:
2022
2022
Historique:
received:
02
09
2022
accepted:
02
11
2022
entrez:
19
12
2022
pubmed:
20
12
2022
medline:
20
12
2022
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 36530356
doi: 10.3389/frai.2022.1034732
pmc: PMC9755752
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
1034732Informations de copyright
Copyright © 2022 Shen, Ghatti, Levkov, Shen, Sen, Rheuban, Enfield, Facteau, Engel and Dowdell.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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