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

doi:10.1109/CONTIE49246.2019.00020

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 proceeding › Conference contribution › peer-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 language	English
Title of host publication	Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019
Editors	Monica Adriana Carreno-Leon, Jesus Andres Sandoval-Bringas, Mario Chacon-Rivas, Francisco Javier Alvarez-Rodriguez
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	56-62
Number of pages	7
ISBN (Electronic)	9781728154367
DOIs	https://doi.org/10.1109/CONTIE49246.2019.00020
State	Published - Oct 2019
Event	2nd International Conference on Inclusive Technologies and Education, CONTIE 2019 - San Jose del Cabo, Mexico Duration: 30 Oct 2019 → 1 Nov 2019

Publication series

Name	Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019

Conference

Conference	2nd International Conference on Inclusive Technologies and Education, CONTIE 2019
Country/Territory	Mexico
City	San Jose del Cabo
Period	30/10/19 → 1/11/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

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

Access to Document

10.1109/CONTIE49246.2019.00020

Cite this

Sulla Torres, J. A., Incalla Nina, C., Rivera Portugal, A. M., Cossio-Bolanos, M., & Gomez Campos, R. (2019). Comparison of Classification Algorithms for the Detection of Bone Weakness in Students Using Anthropometric Data. In M. A. Carreno-Leon, J. A. Sandoval-Bringas, M. Chacon-Rivas, & F. J. Alvarez-Rodriguez (Eds.), Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019 (pp. 56-62). [8971403] (Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CONTIE49246.2019.00020

Sulla Torres, Jose Alfredo ; Incalla Nina, Christian ; Rivera Portugal, Ana Margoth et al. / Comparison of Classification Algorithms for the Detection of Bone Weakness in Students Using Anthropometric Data. Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019. editor / Monica Adriana Carreno-Leon ; Jesus Andres Sandoval-Bringas ; Mario Chacon-Rivas ; Francisco Javier Alvarez-Rodriguez. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 56-62 (Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019).

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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.",

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author = "{Sulla Torres}, {Jose Alfredo} and {Incalla Nina}, Christian and {Rivera Portugal}, {Ana Margoth} and Marco Cossio-Bolanos and {Gomez Campos}, Rossana",

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year = "2019",

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Sulla Torres, JA, Incalla Nina, C, Rivera Portugal, AM, Cossio-Bolanos, M & Gomez Campos, R 2019, Comparison of Classification Algorithms for the Detection of Bone Weakness in Students Using Anthropometric Data. in MA Carreno-Leon, JA Sandoval-Bringas, M Chacon-Rivas & FJ Alvarez-Rodriguez (eds), Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019., 8971403, Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019, Institute of Electrical and Electronics Engineers Inc., pp. 56-62, 2nd International Conference on Inclusive Technologies and Education, CONTIE 2019, San Jose del Cabo, Mexico, 30/10/19. https://doi.org/10.1109/CONTIE49246.2019.00020

Comparison of Classification Algorithms for the Detection of Bone Weakness in Students Using Anthropometric Data. / Sulla Torres, Jose Alfredo; Incalla Nina, Christian; Rivera Portugal, Ana Margoth et al.

Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019. ed. / Monica Adriana Carreno-Leon; Jesus Andres Sandoval-Bringas; Mario Chacon-Rivas; Francisco Javier Alvarez-Rodriguez. Institute of Electrical and Electronics Engineers Inc., 2019. p. 56-62 8971403 (Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Gomez Campos, Rossana

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AB - 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.

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Sulla Torres JA, Incalla Nina C, Rivera Portugal AM, Cossio-Bolanos M, Gomez Campos R. Comparison of Classification Algorithms for the Detection of Bone Weakness in Students Using Anthropometric Data. In Carreno-Leon MA, Sandoval-Bringas JA, Chacon-Rivas M, Alvarez-Rodriguez FJ, editors, Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 56-62. 8971403. (Proceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019). doi: 10.1109/CONTIE49246.2019.00020

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

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Keywords

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