Comprehensive survey of using machine learning in the COVID-19 pandemic

Nora El-Rashidy*, Samir Abdelrazik, Tamer Abuhmed*, Eslam Amer, Farman Ali, Jong Wan Hu*, Shaker El-Sappagh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Since December 2019, the global health population has faced the rapid spreading of coronavirus disease (COVID-19). With the incremental acceleration of the number of infected cases, the World Health Organization (WHO) has reported COVID-19 as an epidemic that puts a heavy burden on healthcare sectors in almost every country. The potential of artificial intelligence (AI) in this context is difficult to ignore. AI companies have been racing to develop innovative tools that contribute to arm the world against this pandemic and minimize the disruption that it may cause. The main objective of this study is to survey the decisive role of AI as a technology used to fight against the COVID-19 pandemic. Five significant applications of AI for COVID-19 were found, including (1) COVID-19 diagnosis using various data types (e.g., images, sound, and text); (2) estimation of the possible future spread of the disease based on the current confirmed cases; (3) association between COVID-19 infection and patient characteristics; (4) vaccine development and drug interaction; and (5) development of supporting applications. This study also introduces a comparison between current COVID-19 datasets. Based on the limitations of the current literature, this review highlights the open research challenges that could inspire the future application of AI in COVID-19.

Original languageEnglish
Article number1155
Pages (from-to)1-44
Number of pages44
JournalDiagnostics
Volume11
Issue number7
DOIs
Publication statusPublished - 24 Jun 2021

Keywords

  • Artificial intelligence
  • COVID_19
  • Deep learning

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