Decoding Deep Learning applications for diagnosis and treatment planning
Jean-Marc Retrouvey1, Richard Scott Conley1
1University of Missouri - Kansas City, Department of Orthodontics (Kansas City/MO, USA).
Introduction:
Artificial Intelligence (AI), Machine Learning and Deep Learning are playing an increasingly significant role in the medical field in the 21st century. These recent technologies are based on the concept of creating machines that have the potential to function as a human brain. It necessitates the gathering of large quantity of data to be processed. Once processed with AI machines, these data have the potential to streamline and improve the capabilities of the medical field in diagnosis and treatment planning, as well as in the prediction and recognition of diseases. These concepts are new to Orthodontics and are currently limited to image processing and pattern recognition.
Objective:
This article exposes and describes the different methods by which orthodontics may benefit from a more widespread adoption of these technologies.
