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Review
. 2022;29(3):1915-1940.
doi: 10.1007/s11831-021-09641-3. Epub 2021 Sep 18.

COVID-19: A Comprehensive Review of Learning Models

Shivam Chahar  1 , Pradeep Kumar Roy  2
Affiliations
Review

COVID-19: A Comprehensive Review of Learning Models

Shivam Chahar et al. Arch Comput Methods Eng. 2022.

Abstract

Coronavirus disease is communicable and inhibits the infected person's immune system. It belongs to the Coronaviridae family and has affected 213 nations and territories so far. Many kinds of studies are being carried out to filter advice and provide oversight to monitor this outbreak. A comparative and brief review was carried out in this paper on research concerning the early identification of symptoms, estimation of the end of the pandemic, and examination of user-generated conversations. Chest X-ray images, abdominal computed tomography scan, tweets shared on social media are several of the datasets used by researchers. Using machine learning and deep learning methods such as K-means clustering, Random Forest, Convolutional Neural Network, Long Short-Term Memory, Auto-Encoder, and Regression approaches, the above-mentioned datasets are processed. The studies on COVID-19 with machine learning and deep learning models with their results and limitations are outlined in this article. The challenges with open future research directions are discussed at the end.

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Conflict of interest statement

Conflict of InterestThere is no conflict of interest

Figures

Fig. 1
Fig. 1
Top ten impacted countries in the world as of July 05,2021
Fig. 2
Fig. 2
Status of covid-19 in India with respect to the world till July 05, 2021
Fig. 3
Fig. 3
The number of new COVID -19 cases and deaths in India
Fig. 4
Fig. 4
Multiple waves of covid-19 outbreak in different countries
Fig. 5
Fig. 5
Covid-19 waves in India by July 05, 2021
Fig. 6
Fig. 6
Steps to extract the relevant articles
See this image and copyright information in PMC

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