• Jasmin Grischke, Lars Johannsmeier, Lukas Eich, Leif Griga, and Sami Haddadin.
• Robokind Robotics for Mankind Foundation, Appelstrasse 30, 30167 Hannover, Germany. Electronic address: grischke.jasmin@robokind.de.
• Dent Mater. 2020 Jun 1; 36 (6): 765-778.

ObjectivesThis paper provides an overview of existing applications and concepts of robotic systems and artificial intelligence in dentistry. This review aims to provide the community with novel inputs and argues for an increased utilization of these recent technological developments, referred to as Dentronics, in order to advance dentistry.MethodsFirst, background on developments in robotics, artificial intelligence (AI) and machine learning (ML) are reviewed that may enable novel assistive applications in dentistry (Sec A). Second, a systematic technology review that evaluates existing state-of-the-art applications in AI, ML and robotics in the context of dentistry is presented (Sec B).ResultsA systematic literature research in pubmed yielded in a total of 558 results. 41 studies related to ML, 53 studies related to AI and 49 original research papers on robotics application in dentistry were included. ML and AI have been applied in dental research to analyze large amounts of data to eventually support dental decision making, diagnosis, prognosis and treatment planning with the help of data-driven analysis algorithms based on machine learning. So far, only few robotic applications have made it to reality, mostly restricted to pilot use cases.SignificanceThe authors believe that dentistry can greatly benefit from the current rise of digital human-centered automation and be transformed towards a new robotic, ML and AI-enabled era. In the future, Dentronics will enhance reliability, reproducibility, accuracy and efficiency in dentistry through the democratized use of modern dental technologies, such as medical robot systems and specialized artificial intelligence. Dentronics will increase our understanding of disease pathogenesis, improve risk-assessment-strategies, diagnosis, disease prediction and finally lead to better treatment outcomes.Copyright © 2020 The Academy of Dental Materials. Published by Elsevier Inc. All rights reserved.

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