Comparison of Classification Algorithms for the Detection of Bone Weakness in Students Using Anthropometric Data

Jose Alfredo Sulla Torres, Christian Incalla Nina, Ana Margoth Rivera Portugal, Marco Cossio-Bolanos, Rossana Gomez Campos

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

Abstract

Low bone mineral density can lead to weak and fragile bones that lead to problems of osteoporosis and fractures in people, early detection can help their treatment. This research compares five data mining algorithms to predict bone weakness in students between 5 and 18 years of age. The methodology used for data processing is CRISP-DM. The accuracy of the algorithms applied in the referenced works with the results obtained with the WEKA data mining tool is discussed. After making the comparison, it was determined that the JRip algorithm was more precise.

Original languageEnglish
Title of host publicationProceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019
EditorsMonica Adriana Carreno-Leon, Jesus Andres Sandoval-Bringas, Mario Chacon-Rivas, Francisco Javier Alvarez-Rodriguez
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages56-62
Number of pages7
ISBN (Electronic)9781728154367
DOIs
StatePublished - Oct 2019
Event2nd International Conference on Inclusive Technologies and Education, CONTIE 2019 - San Jose del Cabo, Mexico
Duration: 30 Oct 20191 Nov 2019

Publication series

NameProceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019

Conference

Conference2nd International Conference on Inclusive Technologies and Education, CONTIE 2019
Country/TerritoryMexico
CitySan Jose del Cabo
Period30/10/191/11/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Anthropometry
  • Bone Mineral Density
  • Data Mining
  • Ramdom-Tree
  • Rules-Jrip
  • Tree-J48

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