Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics

The aim was to find craniofacial morphology patterns in a multivariate cephalometric database using a clustering technique. Cephalometric analysis was performed in a sample of 100 teleradiographs collected from Chilean orthodontic patients. Thirty cephalometric measurements were taken from commonly...

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Autores principales:	Araya-Díaz,Pamela, Ruz,Gonzalo A, Palomino,Hernán M
Lenguaje:	English
Publicado:	Sociedad Chilena de Anatomía 2013
Materias:	Craniofacial patterns Morphological patterns Clustering technique Orthodontics
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-95022013000300053
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spelling	oai:scielo:S0717-950220130003000532013-12-03Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in OrthodonticsAraya-Díaz,PamelaRuz,Gonzalo APalomino,Hernán M Craniofacial patterns Morphological patterns Clustering technique Orthodontics The aim was to find craniofacial morphology patterns in a multivariate cephalometric database using a clustering technique. Cephalometric analysis was performed in a sample of 100 teleradiographs collected from Chilean orthodontic patients. Thirty cephalometric measurements were taken from commonly used analysis. The computed variables were used to perform a clustering analysis with the k-means algorithm to identify patterns of craniofacial morphology. The J48 decision tree was used to analyze each cluster, and the ANOVA test to determine the statistical differences between the clusters. Four clusters were found that had significant differences (P<0.001) in 24 of the 30 variables studied, suggesting that they represent different patterns of craniofacial form. Using the decision tree, 8 of the 30 variables appeared to be relevant for describing the clusters. The clustering analysis is effective in identifying different craniofacial patterns based on a multivariate database. The distinct clusters appear to be caused by differences in the compensation process of the facial structure responding to a genetically determined cranial and mandible form. The proposed method can be applied to several databases, creating specific classifications for each one of them.info:eu-repo/semantics/openAccessSociedad Chilena de AnatomíaInternational Journal of Morphology v.31 n.3 20132013-09-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-95022013000300053en10.4067/S0717-95022013000300053
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Craniofacial patterns Morphological patterns Clustering technique Orthodontics
spellingShingle	Craniofacial patterns Morphological patterns Clustering technique Orthodontics Araya-Díaz,Pamela Ruz,Gonzalo A Palomino,Hernán M Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics
description	The aim was to find craniofacial morphology patterns in a multivariate cephalometric database using a clustering technique. Cephalometric analysis was performed in a sample of 100 teleradiographs collected from Chilean orthodontic patients. Thirty cephalometric measurements were taken from commonly used analysis. The computed variables were used to perform a clustering analysis with the k-means algorithm to identify patterns of craniofacial morphology. The J48 decision tree was used to analyze each cluster, and the ANOVA test to determine the statistical differences between the clusters. Four clusters were found that had significant differences (P<0.001) in 24 of the 30 variables studied, suggesting that they represent different patterns of craniofacial form. Using the decision tree, 8 of the 30 variables appeared to be relevant for describing the clusters. The clustering analysis is effective in identifying different craniofacial patterns based on a multivariate database. The distinct clusters appear to be caused by differences in the compensation process of the facial structure responding to a genetically determined cranial and mandible form. The proposed method can be applied to several databases, creating specific classifications for each one of them.
author	Araya-Díaz,Pamela Ruz,Gonzalo A Palomino,Hernán M
author_facet	Araya-Díaz,Pamela Ruz,Gonzalo A Palomino,Hernán M
author_sort	Araya-Díaz,Pamela
title	Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics
title_short	Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics
title_full	Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics
title_fullStr	Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics
title_full_unstemmed	Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics
title_sort	discovering craniofacial patterns using multivariate cephalometric data for treatment decision making in orthodontics
publisher	Sociedad Chilena de Anatomía
publishDate	2013
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-95022013000300053
work_keys_str_mv	AT arayadiazpamela discoveringcraniofacialpatternsusingmultivariatecephalometricdatafortreatmentdecisionmakinginorthodontics AT ruzgonzaloa discoveringcraniofacialpatternsusingmultivariatecephalometricdatafortreatmentdecisionmakinginorthodontics AT palominohernanm discoveringcraniofacialpatternsusingmultivariatecephalometricdatafortreatmentdecisionmakinginorthodontics
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Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics

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