Artificial intelligence to improve the diagnosis and treatment in Orthodontics: advances, challenges and perspectives. Literature review - Suquilanda Gualán , Pablo Fernando (2025)
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.