4.6 Review

Comprehensive Survey of Using Machine Learning in the COVID-19 Pandemic

期刊

DIAGNOSTICS
卷 11, 期 7, 页码 -

出版社

MDPI
DOI: 10.3390/diagnostics11071155

关键词

artificial intelligence; deep learning; COVID_19

资金

  1. National Research Foundation of Korea (NRF) - Korea government (MSIT) [2020R1A4A4079299]
  2. Incheon National University
  3. National Research Foundation of Korea [2020R1A4A4079299] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

The study identifies the crucial role of AI in combating COVID-19, including diagnostic, epidemic spread prediction, patient characteristics, vaccine development, and supporting application development. Additionally, through comparing current COVID-19 datasets, the review highlights open research challenges for inspiring future AI applications in the pandemic.
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.

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