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Role of intelligent computing in COVID-19 prognosis: A state-of-the-art review
#MMPMID32836916
Swapnarekha H
; Behera HS
; Nayak J
; Naik B
Chaos Solitons Fractals
2020[Sep]; 138
(?): 109947
PMID32836916
show ga
The World Health Organization (WHO) declared novel coronavirus 2019 (COVID-19),
an infectious epidemic caused by SARS-CoV-2, as Pandemic in March 2020. It has
affected more than 40 million people in 216 countries. Almost in all the affected
countries, the number of infected and deceased patients has been enhancing at a
distressing rate. As the early prediction can reduce the spread of the virus, it
is highly desirable to have intelligent prediction and diagnosis tools. The
inculcation of efficient forecasting and prediction models may assist the
government in implementing better design strategies to prevent the spread of
virus. In this paper, a state-of-the-art analysis of the ongoing machine learning
(ML) and deep learning (DL) methods in the diagnosis and prediction of COVID-19
has been done. Moreover, a comparative analysis on the impact of machine learning
and other competitive approaches like mathematical and statistical models on
COVID-19 problem has been conducted. In this study, some factors such as type of
methods(machine learning, deep learning, statistical & mathematical) and the
impact of COVID research on the nature of data used for the forecasting and
prediction of pandemic using computing approaches has been presented. Finally
some important research directions for further research on COVID-19 are
highlighted which may facilitate the researchers and technocrats to develop
competent intelligent models for the prediction and forecasting of COVID-19 real
time data.
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