Artificial intelligence (AI) is rapidly transforming the landscape of dental implantology by enhancing every stage of treatment, from diagnostics and digital planning to intraoperative navigation, outcome prediction, and long-term follow-up. This narrative review explores the current and emerging applications of AI technologies in implant dentistry, with a focus on machine learning, neural networks, and computer vision. It examines how AI is utilized in digital implant planning, surgical navigation, peri-implant disease monitoring, risk assessment, and the prediction of treatment outcomes such as peri-implantitis and implant failure. These innovations contribute to more efficient workflows, more personalized treatment strategies, and improved cost-effectiveness of care. Finally, future perspectives and educational implications of AI integration in clinical implantology are discussed.

AI-Powered Predictive Models in Implant Dentistry: Planning, Risk Assessment, and Outcomes / Neji, G.; Gasparro, R.; Tlili, M.; Dhahri, A.; Khanfir, F.; Sammartino, G.; Aliberti, A.; Campana, M. D.; Ben Amor, F.. - In: JOURNAL OF CLINICAL MEDICINE. - ISSN 2077-0383. - 15:1(2026). [10.3390/jcm15010228]

AI-Powered Predictive Models in Implant Dentistry: Planning, Risk Assessment, and Outcomes

Gasparro R.;Sammartino G.;Campana M. D.;
2026

Abstract

Artificial intelligence (AI) is rapidly transforming the landscape of dental implantology by enhancing every stage of treatment, from diagnostics and digital planning to intraoperative navigation, outcome prediction, and long-term follow-up. This narrative review explores the current and emerging applications of AI technologies in implant dentistry, with a focus on machine learning, neural networks, and computer vision. It examines how AI is utilized in digital implant planning, surgical navigation, peri-implant disease monitoring, risk assessment, and the prediction of treatment outcomes such as peri-implantitis and implant failure. These innovations contribute to more efficient workflows, more personalized treatment strategies, and improved cost-effectiveness of care. Finally, future perspectives and educational implications of AI integration in clinical implantology are discussed.
2026
AI-Powered Predictive Models in Implant Dentistry: Planning, Risk Assessment, and Outcomes / Neji, G.; Gasparro, R.; Tlili, M.; Dhahri, A.; Khanfir, F.; Sammartino, G.; Aliberti, A.; Campana, M. D.; Ben Amor, F.. - In: JOURNAL OF CLINICAL MEDICINE. - ISSN 2077-0383. - 15:1(2026). [10.3390/jcm15010228]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/1026897
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