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

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.

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Publication Details

Journal
Journal of Clinical Medicine
Published
2025-12-27
DOI
https://doi.org/10.3390/jcm15010228
Citations
2
Primary Topic
Dental Radiography and Imaging
Type
article
Field-Weighted Citation Impact
3.58
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article

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

Mohamed Tlili, Faten Khanfir, Faten Ben Amor, Roberta Gasparro et al.
2 citations
Journal of Clinical Medicine
Dental Radiography and Imaging
3.58
article

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

Mohamed Tlili, Faten Khanfir, Faten Ben Amor, Roberta Gasparro, Angelo Aliberti, Aya Dhahri, Maria Domenica Campana, Ghada Neji, Gilberto Sammartino
article en
2 citations

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.

Journal of Clinical MedicineVol. 15(1)
University of Monastir (TN), University of Naples Federico II (IT)
Openalex Percentile: Top 6%
Dental Radiography and Imaging
3.58
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