RT Journal Article
T1 Comprehensive Survey of Using Machine Learning in the COVID-19 Pandemic
A1 El Rashidy, Nora
A1 Abdelrazek, Samir
A1 Abuhmed, Tamer
A1 Amer, Eslam
A1 Ali, Farman
A1 Hu, Jon Wan
A1 El-Sappagh, Shaker
K1 Artificial intelligence
K1 Deep learning
K1 COVID_19
AB 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
PB MDPI
YR 2021
FD 2021
LK http://hdl.handle.net/10347/26659
UL http://hdl.handle.net/10347/26659
LA eng
NO Diagnostics 2021, 11(7), 1155; https://doi.org/10.3390/diagnostics11071155
NO This work was supported by a 2021 Incheon National University Research Grant. This work was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A4A4079299)
DS Minerva
RD 3 may 2026