Machine Learning applications in dentistry: A scoping review
Abstract
This scoping review examines the current landscape of Machine Learning (ML) applications in dentistry, highlighting their potential to revolutionize dental practice and research. The study systematically maps out various ML techniques employed across different dental specialties, including diagnostic imaging, disease prediction, treatment planning, and patient management. By reviewing a broad range of literature, the research identifies key trends, challenges, and future directions in the integration of ML into dental care. The findings demonstrate significant advancements in diagnostic accuracy, personalized treatment plans, and operational efficiency within dental practices. This review underscores the transformative impact of ML on dentistry, advocating for its wider adoption and continuous innovation to improve patient outcomes and streamline dental services.
Keywords
Machine Learning
Dentistry
Diagnostic Imaging
Disease Prediction
Treatment Planning
Patient Management
Scoping Review
Dental Specialties
Healthcare Innovation
Patient Outcomes