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Facial biotype classification for orthodontic treatment planning using an alternative learning algorithm for tree augmented Naive Bayes
BACKGROUND: When designing a treatment in orthodontics, especially for children and teenagers, it is crucial to be aware of the changes that occur throughout facial growth because the rate and direction of growth can greatly affect the necessity of using different treatment mechanics. This paper pre...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9713997/ https://www.ncbi.nlm.nih.gov/pubmed/36456974 http://dx.doi.org/10.1186/s12911-022-02062-7 |
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author | Ruz, Gonzalo A. Araya-Díaz, Pamela Henríquez, Pablo A. |
author_facet | Ruz, Gonzalo A. Araya-Díaz, Pamela Henríquez, Pablo A. |
author_sort | Ruz, Gonzalo A. |
collection | PubMed |
description | BACKGROUND: When designing a treatment in orthodontics, especially for children and teenagers, it is crucial to be aware of the changes that occur throughout facial growth because the rate and direction of growth can greatly affect the necessity of using different treatment mechanics. This paper presents a Bayesian network approach for facial biotype classification to classify patients’ biotypes into Dolichofacial (long and narrow face), Brachyfacial (short and wide face), and an intermediate kind called Mesofacial, we develop a novel learning technique for tree augmented Naive Bayes (TAN) for this purpose. RESULTS: The proposed method, on average, outperformed all the other models based on accuracy, precision, recall, [Formula: see text] , and kappa, for the particular dataset analyzed. Moreover, the proposed method presented the lowest dispersion, making this model more stable and robust against different runs. CONCLUSIONS: The proposed method obtained high accuracy values compared to other competitive classifiers. When analyzing a resulting Bayesian network, many of the interactions shown in the network had an orthodontic interpretation. For orthodontists, the Bayesian network classifier can be a helpful decision-making tool. |
format | Online Article Text |
id | pubmed-9713997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-97139972022-12-02 Facial biotype classification for orthodontic treatment planning using an alternative learning algorithm for tree augmented Naive Bayes Ruz, Gonzalo A. Araya-Díaz, Pamela Henríquez, Pablo A. BMC Med Inform Decis Mak BMC Supplements Reviewed BACKGROUND: When designing a treatment in orthodontics, especially for children and teenagers, it is crucial to be aware of the changes that occur throughout facial growth because the rate and direction of growth can greatly affect the necessity of using different treatment mechanics. This paper presents a Bayesian network approach for facial biotype classification to classify patients’ biotypes into Dolichofacial (long and narrow face), Brachyfacial (short and wide face), and an intermediate kind called Mesofacial, we develop a novel learning technique for tree augmented Naive Bayes (TAN) for this purpose. RESULTS: The proposed method, on average, outperformed all the other models based on accuracy, precision, recall, [Formula: see text] , and kappa, for the particular dataset analyzed. Moreover, the proposed method presented the lowest dispersion, making this model more stable and robust against different runs. CONCLUSIONS: The proposed method obtained high accuracy values compared to other competitive classifiers. When analyzing a resulting Bayesian network, many of the interactions shown in the network had an orthodontic interpretation. For orthodontists, the Bayesian network classifier can be a helpful decision-making tool. BioMed Central 2022-12-01 /pmc/articles/PMC9713997/ /pubmed/36456974 http://dx.doi.org/10.1186/s12911-022-02062-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | BMC Supplements Reviewed Ruz, Gonzalo A. Araya-Díaz, Pamela Henríquez, Pablo A. Facial biotype classification for orthodontic treatment planning using an alternative learning algorithm for tree augmented Naive Bayes |
title | Facial biotype classification for orthodontic treatment planning using an alternative learning algorithm for tree augmented Naive Bayes |
title_full | Facial biotype classification for orthodontic treatment planning using an alternative learning algorithm for tree augmented Naive Bayes |
title_fullStr | Facial biotype classification for orthodontic treatment planning using an alternative learning algorithm for tree augmented Naive Bayes |
title_full_unstemmed | Facial biotype classification for orthodontic treatment planning using an alternative learning algorithm for tree augmented Naive Bayes |
title_short | Facial biotype classification for orthodontic treatment planning using an alternative learning algorithm for tree augmented Naive Bayes |
title_sort | facial biotype classification for orthodontic treatment planning using an alternative learning algorithm for tree augmented naive bayes |
topic | BMC Supplements Reviewed |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9713997/ https://www.ncbi.nlm.nih.gov/pubmed/36456974 http://dx.doi.org/10.1186/s12911-022-02062-7 |
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