Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature review
Descripción del Articulo
The objective of the study was to analyze the impact of artificial intelligence (AI) on diagnosis and treatment in orthodontics, evaluating its advances, benefits, and challenges through a review of recent scientific literature. A bibliographic review was carried out in databases such as PubMed, Sco...
| Autores: | , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2025 |
| Institución: | Universidad de San Martín de Porres |
| Repositorio: | Revistas - Universidad de San Martín de Porres |
| Lenguaje: | español |
| OAI Identifier: | oai:revistas.usmp.edu.pe:article/3188 |
| Enlace del recurso: | https://portalrevistas.aulavirtualusmp.pe/index.php/Rev-Kiru0/article/view/3188 |
| Nivel de acceso: | acceso abierto |
| Materia: | Artificial Intelligence; Diagnosis; Treatment; Orthodontics Inteligencia Artificial; Diagnóstico; Tratamiento; Ortodoncia |
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Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature review Inteligencia artificial en la mejora del diagnóstico y tratamiento en Ortodoncia: avances, desafíos y perspectivas. Revisión de la literatura |
| title |
Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature review |
| spellingShingle |
Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature review Suquilanda Gualán , Pablo Fernando Artificial Intelligence; Diagnosis; Treatment; Orthodontics Inteligencia Artificial; Diagnóstico; Tratamiento; Ortodoncia |
| title_short |
Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature review |
| title_full |
Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature review |
| title_fullStr |
Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature review |
| title_full_unstemmed |
Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature review |
| title_sort |
Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature review |
| dc.creator.none.fl_str_mv |
Suquilanda Gualán , Pablo Fernando Marín Guamán , Marco Antonio |
| author |
Suquilanda Gualán , Pablo Fernando |
| author_facet |
Suquilanda Gualán , Pablo Fernando Marín Guamán , Marco Antonio |
| author_role |
author |
| author2 |
Marín Guamán , Marco Antonio |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Artificial Intelligence; Diagnosis; Treatment; Orthodontics Inteligencia Artificial; Diagnóstico; Tratamiento; Ortodoncia |
| topic |
Artificial Intelligence; Diagnosis; Treatment; Orthodontics Inteligencia Artificial; Diagnóstico; Tratamiento; Ortodoncia |
| description |
The objective of the study was to analyze the impact of artificial intelligence (AI) on diagnosis and treatment in orthodontics, evaluating its advances, benefits, and challenges through a review of recent scientific literature. A bibliographic review was carried out in databases such as PubMed, Scopus, Science Direct, and Google Scholar, using keywords in Spanish and English along with Boolean operators. They were included 42 articles published between 2020 and 2025 that addressed the use of AI in orthodontics, prioritizing studies with scientific and methodological relevance. The implementation of AI in orthodontics has optimized diagnosis and treatment planning through techniques such as convolutional neural networks (CNN), machine learning (ML), and big data-based prediction models. These tools have demonstrated high accuracy in the detection of cephalometric anatomical points, growth analysis, and prediction of orthodontic and orthognathic treatment outcomes. Furthermore, AI has improved clinical decision making, reducing diagnostic time and increasing treatment efficiency. AI has shown high potential to improve diagnosis and treatment in orthodontics, achieving accuracy comparable to that of human experts in identifying anatomical structures and planning treatments. However, its application faces barriers such as lack of standardization, ethical concerns about data privacy, and the need for broader clinical validations. As these challenges should be overcome, AI will establish itself as a key tool in orthodontic practice. |
| publishDate |
2025 |
| dc.date.none.fl_str_mv |
2025-06-30 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
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article |
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publishedVersion |
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https://portalrevistas.aulavirtualusmp.pe/index.php/Rev-Kiru0/article/view/3188 10.24265/kiru.2025.v22n3.04 |
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https://portalrevistas.aulavirtualusmp.pe/index.php/Rev-Kiru0/article/view/3188 |
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10.24265/kiru.2025.v22n3.04 |
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spa |
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spa |
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https://portalrevistas.aulavirtualusmp.pe/index.php/Rev-Kiru0/article/view/3188/3961 https://portalrevistas.aulavirtualusmp.pe/index.php/Rev-Kiru0/article/view/3188/3962 |
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Derechos de autor 2025 Pablo Fernando Suquilanda Gualán , Marco Antonio Marín Guamán https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
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Derechos de autor 2025 Pablo Fernando Suquilanda Gualán , Marco Antonio Marín Guamán https://creativecommons.org/licenses/by/4.0 |
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openAccess |
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application/pdf text/xml |
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Universidad de San Martín de Porres, Facultad de Odontología. |
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Universidad de San Martín de Porres, Facultad de Odontología. |
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KIRU ; Vol. 22 No. 3 (2025): KIRU (JULIO - SETIEMBRE); 191-200 KIRU ISSN electrónico 2410-2717 ISSN Impreso 1812 - 7886; Vol. 22 Núm. 3 (2025): KIRU (JULIO - SETIEMBRE); 191-200 2410-2717 1812-7886 reponame:Revistas - Universidad de San Martín de Porres instname:Universidad de San Martín de Porres instacron:USMP |
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Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature reviewInteligencia artificial en la mejora del diagnóstico y tratamiento en Ortodoncia: avances, desafíos y perspectivas. Revisión de la literatura Suquilanda Gualán , Pablo Fernando Marín Guamán , Marco Antonio Artificial Intelligence; Diagnosis; Treatment; OrthodonticsInteligencia Artificial; Diagnóstico; Tratamiento; OrtodonciaThe objective of the study was to analyze the impact of artificial intelligence (AI) on diagnosis and treatment in orthodontics, evaluating its advances, benefits, and challenges through a review of recent scientific literature. A bibliographic review was carried out in databases such as PubMed, Scopus, Science Direct, and Google Scholar, using keywords in Spanish and English along with Boolean operators. They were included 42 articles published between 2020 and 2025 that addressed the use of AI in orthodontics, prioritizing studies with scientific and methodological relevance. The implementation of AI in orthodontics has optimized diagnosis and treatment planning through techniques such as convolutional neural networks (CNN), machine learning (ML), and big data-based prediction models. These tools have demonstrated high accuracy in the detection of cephalometric anatomical points, growth analysis, and prediction of orthodontic and orthognathic treatment outcomes. Furthermore, AI has improved clinical decision making, reducing diagnostic time and increasing treatment efficiency. AI has shown high potential to improve diagnosis and treatment in orthodontics, achieving accuracy comparable to that of human experts in identifying anatomical structures and planning treatments. However, its application faces barriers such as lack of standardization, ethical concerns about data privacy, and the need for broader clinical validations. As these challenges should be overcome, AI will establish itself as a key tool in orthodontic practice.El objetivo del estudio fue analizar el impacto de la inteligencia artificial (IA) en el diagnóstico y tratamiento en ortodoncia, evaluando sus avances, beneficios y desafíos mediante una revisión de la literatura científica reciente. Se realizó una revisión bibliográfica en bases de datos como PubMed, Scopus, Science Direct y Google Académico, utilizando palabras clave en español e inglés junto con operadores booleanos. Se incluyeron 42 artículos publicados entre 2020 y 2025 que abordaron el uso de IA en ortodoncia, priorizando estudios con relevancia científica y metodológica. La implementación de IA en ortodoncia ha optimizado el diagnóstico y la planificación del tratamiento a través de técnicas como redes neuronales convolucionales (CNN), aprendizaje automático (ML) y modelos de predicción basados en big data. Estas herramientas han demostrado alta precisión en la detección de puntos anatómicos cefalométricos, análisis de crecimiento y predicción de resultados de tratamientos ortodóncicos y ortognáticos. Además, la IA ha mejorado la toma de decisiones clínicas, reduciendo el tiempo de diagnóstico y aumentando la eficiencia en el tratamiento. La IA ha mostrado un alto potencial en la mejora del diagnóstico y tratamiento en ortodoncia, logrando precisión comparable a la de expertos humanos en la identificación de estructuras anatómicas y planificación de tratamientos. No obstante, su aplicación enfrenta barreras como la falta de estandarización, preocupaciones éticas sobre la privacidad de datos y la necesidad de validaciones clínicas más amplias. A medida que se superen estos desafíos, la IA se consolidará como una herramienta clave en la práctica ortodoncia. Universidad de San Martín de Porres, Facultad de Odontología.2025-06-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/xmlhttps://portalrevistas.aulavirtualusmp.pe/index.php/Rev-Kiru0/article/view/318810.24265/kiru.2025.v22n3.04KIRU ; Vol. 22 No. 3 (2025): KIRU (JULIO - SETIEMBRE); 191-200 KIRU ISSN electrónico 2410-2717 ISSN Impreso 1812 - 7886; Vol. 22 Núm. 3 (2025): KIRU (JULIO - SETIEMBRE); 191-2002410-27171812-7886reponame:Revistas - Universidad de San Martín de Porresinstname:Universidad de San Martín de Porresinstacron:USMPspahttps://portalrevistas.aulavirtualusmp.pe/index.php/Rev-Kiru0/article/view/3188/3961https://portalrevistas.aulavirtualusmp.pe/index.php/Rev-Kiru0/article/view/3188/3962Derechos de autor 2025 Pablo Fernando Suquilanda Gualán , Marco Antonio Marín Guamán https://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:revistas.usmp.edu.pe:article/31882025-07-09T22:26:26Z |
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12.605999 |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).