Artificial Intelligence in Orthodontic Treatment Planning and Outcome Prediction

Abstract

Artificial intelligence (AI) has emerged as a transformative tool in orthodontics, offering innovative solutions for treatment planning and outcome prediction. This paper explores the integration of AI technologies, such as machine learning, deep learning, and computer vision, in orthodontic workflows to enhance diagnostic accuracy, optimize treatment strategies, and improve patient outcomes. AI-powered systems analyze large datasets of clinical records, radiographic images, and 3D models to identify patterns and predict treatment results with unprecedented precision. These technologies enable personalized treatment planning by tailoring approaches to individual patient needs, reducing treatment time, and improving overall efficiency. Additionally, predictive models supported by AI can anticipate complications, guide decision-making, and enhance patient communication. Despite its promise, the adoption of AI in orthodontics faces challenges, including data privacy concerns, the need for standardization, and ensuring clinical validation of algorithms. This paper provides a comprehensive review of the current state of AI in orthodontics, highlighting its potential benefits, limitations, and future directions for research and application in clinical practice.