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Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review

The outbreak of novel corona virus 2019 (COVID-19) has been treated as a public health crisis of global concern by the World Health Organization (WHO). COVID-19 pandemic hugely affected countries worldwide raising the need to exploit novel, alternative and emerging technologies to respond to the eme...

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Autores principales: Comito, Carmela, Pizzuti, Clara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8958821/
https://www.ncbi.nlm.nih.gov/pubmed/35534142
http://dx.doi.org/10.1016/j.artmed.2022.102286
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author Comito, Carmela
Pizzuti, Clara
author_facet Comito, Carmela
Pizzuti, Clara
author_sort Comito, Carmela
collection PubMed
description The outbreak of novel corona virus 2019 (COVID-19) has been treated as a public health crisis of global concern by the World Health Organization (WHO). COVID-19 pandemic hugely affected countries worldwide raising the need to exploit novel, alternative and emerging technologies to respond to the emergency created by the weak health-care systems. In this context, Artificial Intelligence (AI) techniques can give a valid support to public health authorities, complementing traditional approaches with advanced tools. This study provides a comprehensive review of methods, algorithms, applications, and emerging AI technologies that can be utilized for forecasting and diagnosing COVID-19. The main objectives of this review are summarized as follows. (i) Understanding the importance of AI approaches such as machine learning and deep learning for COVID-19 pandemic; (ii) discussing the efficiency and impact of these methods for COVID-19 forecasting and diagnosing; (iii) providing an extensive background description of AI techniques to help non-expert to better catch the underlying concepts; (iv) for each work surveyed, give a detailed analysis of the rationale behind the approach, highlighting the method used, the type and size of data analyzed, the validation method, the target application and the results achieved; (v) focusing on some future challenges in COVID-19 forecasting and diagnosing.
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spelling pubmed-89588212022-03-28 Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review Comito, Carmela Pizzuti, Clara Artif Intell Med Article The outbreak of novel corona virus 2019 (COVID-19) has been treated as a public health crisis of global concern by the World Health Organization (WHO). COVID-19 pandemic hugely affected countries worldwide raising the need to exploit novel, alternative and emerging technologies to respond to the emergency created by the weak health-care systems. In this context, Artificial Intelligence (AI) techniques can give a valid support to public health authorities, complementing traditional approaches with advanced tools. This study provides a comprehensive review of methods, algorithms, applications, and emerging AI technologies that can be utilized for forecasting and diagnosing COVID-19. The main objectives of this review are summarized as follows. (i) Understanding the importance of AI approaches such as machine learning and deep learning for COVID-19 pandemic; (ii) discussing the efficiency and impact of these methods for COVID-19 forecasting and diagnosing; (iii) providing an extensive background description of AI techniques to help non-expert to better catch the underlying concepts; (iv) for each work surveyed, give a detailed analysis of the rationale behind the approach, highlighting the method used, the type and size of data analyzed, the validation method, the target application and the results achieved; (v) focusing on some future challenges in COVID-19 forecasting and diagnosing. Elsevier B.V. 2022-06 2022-03-28 /pmc/articles/PMC8958821/ /pubmed/35534142 http://dx.doi.org/10.1016/j.artmed.2022.102286 Text en © 2022 Elsevier B.V. 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 Article
Comito, Carmela
Pizzuti, Clara
Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review
title Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review
title_full Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review
title_fullStr Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review
title_full_unstemmed Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review
title_short Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review
title_sort artificial intelligence for forecasting and diagnosing covid-19 pandemic: a focused review
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8958821/
https://www.ncbi.nlm.nih.gov/pubmed/35534142
http://dx.doi.org/10.1016/j.artmed.2022.102286
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