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

Shaker El–Sappagh, Tamer Abuhmed, Jong Wan Hu, Farman Ali, Nora El-Rashidy, Eslam Amer, Samir Abdelrazik
2021-06-24

SCID:  54.1/zxet5m5h
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.
Publication Details
Publication Date
2021-06-24
Journal
Publisher
ISSN
Access Type
Author Information
Authors
Shaker El–Sappagh
Tamer Abuhmed
Jong Wan Hu
Farman Ali
Nora El-Rashidy
Eslam Amer
Samir Abdelrazik
Explore More Research
Use the citation graph to discover related papers and expand your research horizons.
Click any node to explore
Download PDF
100%