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

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

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaProceedings - 2019 International Conference on Inclusive Technologies and Education, CONTIE 2019
EditoresMonica Adriana Carreno-Leon, Jesus Andres Sandoval-Bringas, Mario Chacon-Rivas, Francisco Javier Alvarez-Rodriguez
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas56-62
Número de páginas7
ISBN (versión digital)9781728154367
DOI
EstadoPublicada - oct. 2019
Publicado de forma externa
Evento2nd International Conference on Inclusive Technologies and Education, CONTIE 2019 - San Jose del Cabo, México
Duración: 30 oct. 20191 nov. 2019

Serie de la publicación

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

Conferencia

Conferencia2nd International Conference on Inclusive Technologies and Education, CONTIE 2019
País/TerritorioMéxico
CiudadSan Jose del Cabo
Período30/10/191/11/19

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