Clasificación de la densidad mineral ósea utilizando técnicas de aprendizaje automático en niños y adolescentes según edad y sexo

Translated title of the contribution: Classification of bone mineral density using automatic learning techniques in children and adolescents according to age and sex

Jose Alfredo Sulla Torres, Alan Bedoya-Carrillo, Rossana Gomez-Campos, Marco Cossio-Bolaños

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

Abstract

Bone health is a field that has become very important in recent years, especially in diseases related to bones, since they are becoming more common among humans. Osteoporosis currently causes an estimated 8.9 million fractures annually. Bone mineral density (BMD) and bone mineral content (BMC) are indicators that can diagnose the problem of bone health. The objective of this study is to classify BMD in children and adolescents using automatic learning techniques. A descriptive cross-sectional study was developed. We studied 660 schoolchildren from two educational centers with an age range of 6 to 18 years from the province of Arequipa (Peru). Anthropometric variables were evaluated. The BMD and CMO were determined. The Body Mass Index (BMI) was calculated, and a comparative study was made of 9 machine learning algorithms related to the subject. These include decision trees, bayesian networks, decision and regression tables. Random Forest's classification algorithm is 94.87%. This algorithm allowed to implement a software. This tool allows to calculate the bone health of schoolchildren between 6 to 18 years. The algorithm obtained can be implemented from a prediction software that allows the classification and prevention of the deterioration of the bone health of children and adolescents.

Translated title of the contributionClassification of bone mineral density using automatic learning techniques in children and adolescents according to age and sex
Original languageSpanish
Title of host publication17th LACCEI International Multi-Conference for Engineering, Education, and Technology
Subtitle of host publication"Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019
PublisherLatin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)9780999344361
StatePublished - 2019
Externally publishedYes
Event17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 - Montego Bay, Jamaica
Duration: 24 Jul 201926 Jul 2019

Publication series

NameProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume2019-July
ISSN (Electronic)2414-6390

Conference

Conference17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019
Country/TerritoryJamaica
CityMontego Bay
Period24/07/1926/07/19

Bibliographical note

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

Fingerprint

Dive into the research topics of 'Classification of bone mineral density using automatic learning techniques in children and adolescents according to age and sex'. Together they form a unique fingerprint.

Cite this