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Machine Learning in Fighting Pandemics: A COVID-19 Case Study

  • Mufti Mahmud*
  • , M. Shamim Kaiser
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

43 Scopus citations

Abstract

In today’s digitised world, machine learning (ML) has been playing a very important role in identifying patterns from the ever-growing amount of data made available by the devices and sensors used in the day-to-day activities. Applications of ML have enriched many fields directly connected to our daily lives including education, finance, governance, healthcare, security and surveillance, etc. Its applications can also be extended in facilitating the management of pandemics, especially when the world is experiencing an unprecedented pandemic caused by the novel coronavirus disease (COVID-19). This chapter aims to provide an account of how ML can be utilised in fighting pandemics in general, with a focus on the COVID-19.

Original languageEnglish
Title of host publicationLecture Notes on Data Engineering and Communications Technologies
PublisherSpringer Science and Business Media Deutschland GmbH
Pages77-81
Number of pages5
DOIs
StatePublished - 2021
Externally publishedYes

Publication series

NameLecture Notes on Data Engineering and Communications Technologies
Volume60
ISSN (Print)2367-4512
ISSN (Electronic)2367-4520

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Disease spread management
  • Infection management
  • Multi-sensor data
  • Novel coronavirus
  • Pandemic management

ASJC Scopus subject areas

  • Information Systems
  • Media Technology
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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