Aplicación de la inteligencia artificial en el diagnóstico cefalométrico en ortodoncia. Revisión de la literatura

Abstract

This research aims to report on the application of artificial intelligence to improve diagnostic and cephalometric accuracy in orthodontics through the integration of artificial intelligence (AI)-based systems. It uses a documentary, descriptive, and cross-sectional approach based on the collection of information on the application of artificial intelligence in cephalometric diagnosis in orthodontics. Although AI is a broad topic with numerous categories, there are two types: symbolic AI and machine learning. Symbolic AI refers to a set of methods for constructing algorithms in a way that is understandableto humans. Deep learning is a type of machine learning in which a computer recognizes features in data. This article aims to discuss the scope and performance of these AI-based models that have been applied in various aspects of orthodontic diagnosis, treatment planning, clinical decision-making, and prognosis prediction. In conclusion, the impact of AI on orthodontics is remarkable, given that this specialty makes particular use of diagnostic tools that aid clinical decision-making. The studies reviewed agree that AI systems provide effective, reliable results with a promising future, as they facilitate complex tasks, are fast, and can support less experienced dentists. In conclusion, the impact of AI on orthodontics is remarkable, given that this specialty makes particular use of diagnostic tools that aid clinical decision-making. The studies reviewed agree that AI systems provide effective, reliable results with a promising future, as they facilitate complex tasks, are fast, and can support less experienced dentists, saving time and improving the quality of care.