Inteligencia artificial y sus aplicaciones en ortodoncia - Una revisión

Voleti Sri Srujana Aravinda, Manem Jaganath Venkat

Resumen


INTRODUCCIÓN: Las últimas décadas hemos percibido variaciones masivas en nuestra profesión. La llegada de nuevas opciones estéticas en ortodoncia, el cambio hacia un flujo de trabajo completamente digital, el desarrollo de dispositivos de anclaje temporal y nuevos métodos de obtención de imágenes ofrecen tanto a los pacientes como a los profesionales un enfoque novedoso en el cuidado de la ortodoncia. OBJETIVO: Esta revisión tiene como objetivo proporcionar una visión general de la evidencia existente sobre el uso de inteligencia artificial (IA), aprendizaje automático (ML) y su traducción a la práctica clínica de ortodoncia. Su objetivo es determinar las aplicaciones de la Inteligencia Artificial (IA) en el campo de la Ortodoncia, evaluar sus beneficios y discutir sus potenciales implicaciones en esta especialidad.  MATERIAL Y MÉTODOS: La literatura para este artículo fue identificada y seleccionada mediante una búsqueda exhaustiva en bases de datos electrónicas como PubMed, Medline, Embase, Cochrane, Google Scholar, Scopus, Web of Science publicadas durante las últimas dos décadas (enero de 2000 - diciembre de 2021). RESULTADOS: La IA se implementa ampliamente en una amplia gama de ortodoncia para predecir las extracciones de ortodoncia necesarias para los tratamientos de ortodoncia. Los análisis y la detección automatizados de puntos de referencia, la evaluación del crecimiento y el desarrollo, el diagnóstico y la planificación del tratamiento fueron los más comúnmente estudiados. CONCLUSIÓN: Ha habido un aumento exponencial en el número de estudios que involucran diversas aplicaciones de ortodoncia de inteligencia artificial y aprendizaje automático. La IA también puede mejorar la precisión de los tratamientos de ortodoncia, ayudando así al ortodoncista a trabajar de forma más precisa y eficiente.

Recibido: 29/11/2024
Aceptado: 03/01/2025


Palabras clave


Inteligencia artificial; Aprendizaje automático; Ortodoncia; redes neuronales y ortodoncia; abordaje híbrido y ortodoncia.

Texto completo:

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Referencias


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