Falk Schwendicke|Wojciech Samek|Joachim Krois
Artificial Intelligence in Dentistry: Chances and Challenges
Charité - Universitätsmedizin Berlin|Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute|Charité - Universitätsmedizin Berlin
term artificial intelligence ai refers idea machines capable performing human tasks subdomain ai machine learning ml learns intrinsic statistical patterns data eventually cast predictions unseen data deep learning ml technique using multilayer mathematical operations learning inferring complex data like imagery succinct narrative review describes application limitations possible future aibased dental diagnostics treatment planning conduct example image analysis prediction making record keeping well dental research discovery aibased applications streamline care relieving dental workforce laborious routine tasks increasing health lower costs broader population eventually facilitate personalized predictive preventive participatory dentistry however ai solutions large entered routine dental practice mainly due 1 limited data availability accessibility structure comprehensiveness 2 lacking methodological rigor standards development 3 practical questions around value usefulness solutions also ethics responsibility ai application dentistry demonstrate tangible value example improving access quality care increasing efficiency safety services empowering enabling patients supporting medical research increasing sustainability individual privacy rights autonomy need put front center shift centralized distributedfederated learning may address improving scalability robustness lastly trustworthiness generalizability dental ai solutions need guaranteed implementation continuous human oversight standards grounded evidencebased dentistry expected methods visualize interpret explain logic behind ai solutions contribute explainable ai dental education need accompany introduction clinical ai solutions fostering digital literacy future dental workforce