Unveiling the prospects and challenges of artificial intelligence in implant dentistry. A systematic review


Submitted: 26 September 2023
Accepted: 5 January 2024
Published: 5 March 2024
Abstract Views: 288
PDF: 240
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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.


Banerjee, T. N., Paul, P., Debnath, A., & Banerjee, S. (2024). Unveiling the prospects and challenges of artificial intelligence in implant dentistry. A systematic review. Journal of Osseointegration, 16(1), 53–60. https://doi.org/10.23805/JO.2024.605

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