A Topological Data Analysis Approach to the COVID-19

Zhichao Lu, Heng Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Topological data analysis (TDA) has emerged as a method for understanding data clouds by extracting and comparing the structure of datasets. This paper applies one of the TDA instruments available which is called the Mapper algorithm to analyze the COVID-19 data in China. The Mapper graphs generated by the algorithm successfully reflect the development of COVID-19 across China and provide a relatively complete visualization of the pandemic. Experimental results indicate that the proposed method may have the potential to become a robust predictive tool for the spread of the coronavirus.

Original languageEnglish
Title of host publicationIEEE 10th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022
EditorsBing Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages469-473
Number of pages5
ISBN (Electronic)9781665422079
DOIs
Publication statusPublished - 2022
Event10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022 - Chongqing, China
Duration: 17 Jun 202219 Jun 2022

Publication series

NameIEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)
Volume2022-June
ISSN (Print)2693-2865

Conference

Conference10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022
Country/TerritoryChina
CityChongqing
Period17/06/2219/06/22

Keywords

  • COVID-19
  • Mapper
  • Topological Data Analysis
  • Visualization

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