Applications of artificial intelligence in dental implant detection and planning: A narrative review
1 Researcher, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
2 Researcher, School of Dentistry, Tehran University of Medical Sciences, Tehran, Iran.
Review
Open Access Research Journal of Biology and Pharmacy, 2026, 17(01), 029-036.
Article DOI: 10.53022/oarjbp.2026.17.1.0033
Publication history:
Received on 02 April 2026; revised on 12 May 2026; accepted on 15 May 2026
Abstract:
In recent decades, Implant dentistry has seen remarkable development across the globe. The field of implantology has revolutionized dentistry significantly, especially in the rehabilitation of single, complete and partial edentulism. Conventionally, practitioners utilize periapical radiographs, panoramic imaging, CBCT scans and periapical radiographs to assess implant locations. CBCT is particularly important as it provides 3D data about density, width, bone height and closeness to vital anatomical structures. This narrative review explores the current applications of AI in dental implant planning and detection, with emphasis on cone-beam computed tomography (CBCT), intraoral scanning, and image-guided system. Machine learning and deep learning enable automated segmentation, virtual planning, and improved surgical precision. Despite strong performance, limitations include data dependency, low transparency, and need for validation. Future work will focus on multimodal systems, real-time guidance, and robotic-assisted implant placement. Overall, AI is making implant dentistry more precise, efficient, and data-driven.
Keywords:
Artificial intelligence; Dentistry; Dental Implant; Prognosis; Planning
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Copyright © 2026 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0