This book reviews all aspects of the use of machine learning in contemporary dentistry, clearly explaining its significance for dental imaging, oral diagnosis and treatment, dental designs, and dental research. Machine learning is an emerging field of artificial intelligence research and practice in which computer agents are employed to improve perception, cognition, and action based on their ability to "learn", for example through use of big data techniques. Its application within dentistry is designed to promote personalized and precision patient care, with enhancement of diagnosis and treatment planning. In this book, readers will find up-to-date information on different machine learning tools and their applicability in various dental specialties. The selected examples amply illustrate the opportunities to employ a machine learning approach within dentistry while also serving to highlight the associated challenges. Machine Learning in Dentistry will be of value for alldental practitioners and researchers who wish to learn more about the potential benefits of using machine learning techniques in their work.

Machine Learning for Dental Imaging: Machine Learning for CBCT Segmentation of Craniofacial 3D Image

Machine Learning for Automatic Landmark Detection of 3D Imaging
Machine Learning for Generating Dental CT from Magnetic Resonance Imaging (MRI)
Machine Learning for 2D Dynamic Facial Photographs. Machine Learning for Oral Diagnosis and Treatment: Machine Learning for Orthodontic Diagnosis and Treatment Planning
Machine Learning for Diagnosis of Periodontal Diseases
Machine Learning for Oral Microbiome
Machine Learning for Characterization of Craniofacial Anomaly
Machine  Learning for Orthognathic Surgery
Machine Learning for Bone Tissue Engineering. Machine Learning and Dental Designs: Machine Learning for Orthodontic CAD/CAM Technologies
Machine  Learning for Design of Dental Implants
Machine Learning for Optimization of Dental Material Processing. Machine Learning Supporting Dental Research: Machine Learningfor Data Mining in Teledentistry
Machine Learning for Evidence-Based Literature Search
Machine Learning in Genetics and Genomics
Machine Learning and Finite Element Modeling.