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Application of Artificial Intelligence in DentalImplantology: A Narrative Review
Armin Jamshidi, Aminollah Khormali, Negin Soghli, Patricia A. Miguez
How is Artificial Intelligence (AI)performing in treatment planningand evaluation of dental implantsuccess?
We conducted a narrative reviewof published papers to synthesizeand evaluate AI applications indental implantology, highlightingkey advantages, limitations, andfuture directions.
Google Scholar and PubMed were used to search for published papersin English between the years 2020 and 2025.
Only original articles were included for the screening.
Three evaluators (AJ, AK, and NS) screened all studies.
Studies closely aligning with the focus of the review were included.
Rapidly growing trend since 2020
Main uses of AI and implants: Automating image-based tasks, Predicting clinical outcomes, Helping with treatment planning
Accuracy ~ 90%
Area under curve: 0.9 - 0.99
Current promises with AI: Clinical tools, Recognizing treatment outcomes, Personalizing care
Current challenges with AI: Standardization across imaging modalities, External validation, Handling low quality radiographs, Integration of multi-modal data, Unrepresentative datasets for predictive accuracy
Progress with AI can strengthen clinical applicability and reliability.
