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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Publicado en:Artificial Intelligence in Medicine Vol. 128
Autores principales: Comito, Carmela, Pizzuti, Clara
Formato: review Journal Article
Publicado: Elsevier B.V. Jun2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2022
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      pub: Elsevier B.V.
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        atl: Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review.
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          Comito, Carmela
          Pizzuti, Clara
        affil: National Research Council of Italy (CNR), Institute for High Performance Computing and Networking (ICAR), Rende, Italy
      sug:
      ab: 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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        review
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    language: English
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