The Number of Confirmed Cases of Covid-19 by Using Machine Learning: Methods and Challenges

Overview

Journal Arch Comput Methods Eng

Date 2020 Aug 25

PMID 32837183

Citations 27

Authors

Amir Ahmad

Sunita Garhwal

Santosh Kumar Ray

Gagan Kumar

Sharaf Jameel Malebary

Omar Mohammed Barukab

Affiliations

Soon will be listed here.

Abstract

Covid-19 is one of the biggest health challenges that the world has ever faced. Public health policy makers need the reliable prediction of the confirmed cases in future to plan medical facilities. Machine learning methods learn from the historical data and make predictions about the events. Machine learning methods have been used to predict the number of confirmed cases of Covid-19. In this paper, we present a detailed review of these research papers. We present a taxonomy that groups them in four categories. We further present the challenges in this field. We provide suggestions to the machine learning practitioners to improve the performance of machine learning methods for the prediction of confirmed cases of Covid-19.

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