Unveiling the prospects and challenges of artificial intelligence in implant dentistry. A systematic review
https://doi.org/10.23805/JO.2024.605
Accepted: 5 January 2024
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
ABSTRACT
Aim This systematic review aims to comprehensively evaluate the impact of AI (artificial intelligence) on implant dentistry through an analysis of studies published within the last decade.
Materials and methods A thorough search was conducted across reputable databases - MEDLINE/PubMed, Web of Science, and Scopus - using keywords like "Artificial intelligence in Dentistry," "Dental Implants," "Prosthodontics," and "Implantology." This strategy ensured the inclusion of studies directly pertinent to AI's role in implant dentistry. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines ensured transparency in the review process, a total of 154 articles were screened various databases [MEDLINE/PubMed, Web of Science, Scopus]. A meticulous search yielded 12 eligible studies that encompass applications in implant planning, identification, prognosis, and crown design, maintaining the systematic review's quality benchmarks.
Results The integration of AI's predictive capabilities with patient-specific data offers the promise of improved patient care quality. Among the 12 articles, 7 (58.33%) focus on AI-assisted identification of dental implants using IOPA or panoramic radiographs, 3 (25%) on implant planning, 1 (8.3%) on implant prognosis, and 1 (8.3%) on crown design for dental implants. All the studies showed more than 90% accuracy in identifying dental implant systems using AI.
Conclusion This systematic review underscores AI's substantial potential for revolutionizing implant dentistry. While the advantages are compelling, a balanced approach is crucial to tackle challenges. Addressing concerns related to data quality, clinical validation, ethics, and regulatory frameworks is imperative for the responsible and effective integration of AI in implant dentistry.
Copyright (c) 2024 Ariesdue
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The Journal of Osseointegration has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Downloads
Citations
