Abstract

The Role of Artificial Intelligence in Personalized and Patient-Centered Orthodontics

by Leonardi Rosalia Maria

Artificial Intelligence (AI) in orthodontics is finding increasingly broad and relevant applications, thanks to its ability to process large amounts of clinical data and radiographic or photographic images quickly and accurately. Among the main fields of application are: 1. Diagnosis and treatment planning; 2. Imaging and image-based diagnostics; 3. Clear aligners and orthodontic appliances; 4. Remote patient monitoring; 5. Decision support; 6. Personalization and Precision. This last point is part of a broader vision of predictive, preventive, personalized, and participatory medicine (‘P4’), which has long been hoped for in the treatment of our patients. Personalized medicine and precision medicine are terms often used interchangeably to describe a therapeutic approach tailored to each individual, but with a subtle difference: precision medicine focuses more on unique biological characteristics (genetics, microbiome), while personalized medicine includes, in addition to these biological aspects, also the experiences, lifestyle, and socio-cultural context of the patient in order to define more effective and comprehensive care and prevention pathways. Both rely on artificial intelligence, which plays a fundamental role in making this possible, thanks to its ability to analyze and interpret enormous volumes of data with unprecedented speed and accuracy, improving diagnostic accuracy and optimizing therapies.The presentation will describe the potential and possible practical uses in personalized clinical orthodontics for more appropriate orthodontic treatment of patients.

Learning Objectives

After this lecture, you will be able to explore the difference between machine learning, deep learning, and traditional software.
After this lecture, you will be able to deepen your knowledge of the practical applications of artificial intelligence (AI) in orthodontics
After this lecture, you will be able to objectively evaluate the benefits for both the clinician and the patient.