Predicción de riesgo de osteoporosis en escolares utilizando minería de datos

Christian Incalla-Nina, Renzo Portilla-Arias, Doris Ccama-Yana, Britsel Calluchi-Arocutipa, Jose Alfredo Sulla Torres

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Low bone mineral density and loss of bone tissue can result in weak and fragile bones that are characteristic of osteoporosis disease. This common public health problem has no symptoms. Osteoporosis is a disease considered as the global epidemic of the 21st century. This disease is usually pronounced in children and adolescents as osteopenia. The following article aims to classify and detect bone mineral density in children and adolescents from a range of 6 to 11 years of age by pre-processing data with the KDD process and using association rules as a classification technique. Subsequently, the results are compared with the database of a real densitometer. The results show the statistics of children who have osteoporosis and osteopenia.

Título traducido de la contribuciónPredicting the risk of osteoporosis in schoolchildren using data mining
Idioma originalEspañol
Título de la publicación alojada17th LACCEI International Multi-Conference for Engineering, Education, and Technology
Subtítulo de la publicación alojada"Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019
EditorialLatin American and Caribbean Consortium of Engineering Institutions
ISBN (versión digital)9780999344361
DOI
EstadoPublicada - 2019
Evento17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 - Montego Bay, Jamaica
Duración: 24 jul. 201926 jul. 2019

Serie de la publicación

NombreProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volumen2019-July
ISSN (versión digital)2414-6390

Conferencia

Conferencia17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019
País/TerritorioJamaica
CiudadMontego Bay
Período24/07/1926/07/19

Nota bibliográfica

Publisher Copyright:
© 2019 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

Palabras clave

  • Bone mineral density
  • Data Mining
  • Osteoporosis
  • Prediction

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