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A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic
While the world has experience with many different types of infectious diseases, the current crisis related to the spread of COVID-19 has challenged epidemiologists and public health experts alike, leading to a rapid search for, and development of, new and innovative solutions to combat its spread....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7547637/ https://www.ncbi.nlm.nih.gov/pubmed/33071481 http://dx.doi.org/10.1016/j.chaos.2020.110337 |
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author | Rasheed, Jawad Jamil, Akhtar Hameed, Alaa Ali Aftab, Usman Aftab, Javaria Shah, Syed Attique Draheim, Dirk |
author_facet | Rasheed, Jawad Jamil, Akhtar Hameed, Alaa Ali Aftab, Usman Aftab, Javaria Shah, Syed Attique Draheim, Dirk |
author_sort | Rasheed, Jawad |
collection | PubMed |
description | While the world has experience with many different types of infectious diseases, the current crisis related to the spread of COVID-19 has challenged epidemiologists and public health experts alike, leading to a rapid search for, and development of, new and innovative solutions to combat its spread. The transmission of this virus has infected more than 18.92 million people as of August 6, 2020, with over half a million deaths across the globe; the World Health Organization (WHO) has declared this a global pandemic. A multidisciplinary approach needs to be followed for diagnosis, treatment and tracking, especially between medical and computer sciences, so, a common ground is available to facilitate the research work at a faster pace. With this in mind, this survey paper aimed to explore and understand how and which different technological tools and techniques have been used within the context of COVID-19. The primary contribution of this paper is in its collation of the current state-of-the-art technological approaches applied to the context of COVID-19, and doing this in a holistic way, covering multiple disciplines and different perspectives. The analysis is widened by investigating Artificial Intelligence (AI) approaches for the diagnosis, anticipate infection and mortality rate by tracing contacts and targeted drug designing. Moreover, the impact of different kinds of medical data used in diagnosis, prognosis and pandemic analysis is also provided. This review paper covers both medical and technological perspectives to facilitate the virologists, AI researchers and policymakers while in combating the COVID-19 outbreak. |
format | Online Article Text |
id | pubmed-7547637 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75476372020-10-13 A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic Rasheed, Jawad Jamil, Akhtar Hameed, Alaa Ali Aftab, Usman Aftab, Javaria Shah, Syed Attique Draheim, Dirk Chaos Solitons Fractals Review While the world has experience with many different types of infectious diseases, the current crisis related to the spread of COVID-19 has challenged epidemiologists and public health experts alike, leading to a rapid search for, and development of, new and innovative solutions to combat its spread. The transmission of this virus has infected more than 18.92 million people as of August 6, 2020, with over half a million deaths across the globe; the World Health Organization (WHO) has declared this a global pandemic. A multidisciplinary approach needs to be followed for diagnosis, treatment and tracking, especially between medical and computer sciences, so, a common ground is available to facilitate the research work at a faster pace. With this in mind, this survey paper aimed to explore and understand how and which different technological tools and techniques have been used within the context of COVID-19. The primary contribution of this paper is in its collation of the current state-of-the-art technological approaches applied to the context of COVID-19, and doing this in a holistic way, covering multiple disciplines and different perspectives. The analysis is widened by investigating Artificial Intelligence (AI) approaches for the diagnosis, anticipate infection and mortality rate by tracing contacts and targeted drug designing. Moreover, the impact of different kinds of medical data used in diagnosis, prognosis and pandemic analysis is also provided. This review paper covers both medical and technological perspectives to facilitate the virologists, AI researchers and policymakers while in combating the COVID-19 outbreak. Elsevier Ltd. 2020-12 2020-10-10 /pmc/articles/PMC7547637/ /pubmed/33071481 http://dx.doi.org/10.1016/j.chaos.2020.110337 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Review Rasheed, Jawad Jamil, Akhtar Hameed, Alaa Ali Aftab, Usman Aftab, Javaria Shah, Syed Attique Draheim, Dirk A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic |
title | A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic |
title_full | A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic |
title_fullStr | A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic |
title_full_unstemmed | A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic |
title_short | A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic |
title_sort | survey on artificial intelligence approaches in supporting frontline workers and decision makers for the covid-19 pandemic |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7547637/ https://www.ncbi.nlm.nih.gov/pubmed/33071481 http://dx.doi.org/10.1016/j.chaos.2020.110337 |
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