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Forecasting COVID-19 Pandemic Using Linear Regression Model

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Digital Transformation Technology

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 224))

Abstract

During the ongoing worldwide crisis, researchers, clinicians, and medical care specialists around the world continue looking for another innovation to help in handling the COVID-19 pandemic. The proof of Machine Learning (ML) and Artificial Intelligence (AI) application on the past pestilence empower scientists by giving another point to battle against the novel Coronavirus episode. This paper intends to thoroughly audit the part of AI and ML as one critical technique in anticipating SARS-CoV-2 and its related epidemic. Coronavirus is an irresistible illness, and it does serious harm to the lungs. Coronavirus causes disease in people and has executed numerous individuals in the whole world. Nonetheless, this infection is accounted for as a pandemic by the World Health Organization. (WHO) and all nations are attempting to control and lockdown all spots. This work's main principle goal is to predicting the spread of COVID-19 across Egypt and analyzing the development rates. For this aim, we access real datasets collected from Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). And European Union open dataset. We have implemented the results by using R Language.

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Author information

Authors and Affiliations

  1. Department of Computers and Information Systems, Sadat Academy, Cairo, Egypt

    Heba M. Sabri, Ahmad M. Gamal El-Din & Lamia Aladel

Authors
  1. Heba M. Sabri
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  2. Ahmad M. Gamal El-Din
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  3. Lamia Aladel
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Editor information

Editors and Affiliations

  1. Canadian International College, Sadat Academy for Management Sciences, New Cairo, Egypt

    Dalia A. Magdi

  2. Department of Information Systems, Helwan University, Cairo, Egypt

    Yehia K. Helmy

  3. Dr. of Computer Sciences, Ahram Canadian University, Cairo, Egypt

    Mohamed Mamdouh

  4. Director, Global Knowledge Research Foundation, Ahmedabad, India

    Amit Joshi

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Sabri, H.M., Gamal El-Din, A.M., Aladel, L. (2022). Forecasting COVID-19 Pandemic Using Linear Regression Model. In: Magdi, D.A., Helmy, Y.K., Mamdouh, M., Joshi, A. (eds) Digital Transformation Technology. Lecture Notes in Networks and Systems, vol 224. Springer, Singapore. https://doi.org/10.1007/978-981-16-2275-5_32

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