Title
Predicting the risk of osteoporosis in schoolchildren using data mining
Other title
Predicción de riesgo de osteoporosis en escolares utilizando minería de datos.
Date Issued
2019
Access level
open access
Resource Type
conference paper
Author(s)
Universidad Nacional de San Agustín de Arequipa
Publisher(s)
Latin American and Caribbean Consortium of Engineering Institutions
Abstract
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.
Volume
2019-July
Language
Spanish
OCDE Knowledge area
Ingeniería de sistemas y comunicaciones
Subjects
Scopus EID
2-s2.0-85073630800
ISBN
9780999344361
Source
Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Resource of which it is part
Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
ISSN of the container
24146390
ISBN of the container
978-099934436-1
Sponsor(s)
A la Universidad Nacional de San Agustín de Arequipa, que ha financiado el proyecto con número de contrato 42-2017-UNSA otorgado para la realización del artículo.
Sources of information:
Directorio de Producción Científica
Scopus