As Artificial Intelligence (AI) and Machine Learning (ML) become increasingly ubiquitous in health care, its integration into orthodontics in inevitable. Input data for AI/ML include images, EHR, wearables, biological data, and payer records. These, in turn, generate information for use in diagnostics, preventive medicine, precision medicine, prognostics, and reduction of adverse events. Advances in the use of ML in orthodontics have focused on image processing (landmark identification, cephalometric analyses and segmentation) and diagnostic support (e.g. skeletal classification, skeletal maturation and CFA). Besides discussing current discoveries and uses of AI/ML, Dr. Kapila will highlight innovations of AI/ML in clinical decision support (extraction vs non-extraction, optimized biomechanics, OSA therapy), treatment outcomes and prognostics, risk prediction (root resorption and periodontal support loss) and patient stratification (e.g. TMDs).
Learning Objectives:
After this session, attendees will be able to:
Understand data sources and methods used for AI/ML in health care and specifically in orthodontics.
Recall the current status of AI/ML in orthodontics in image processing and diagnostic support.
Comprehend innovations that will facilitate the further integration of AI/ML into orthodontics.
