Harnessing AI in prosthodontics and implant dentistry: An umbrella review of systematic evidence
Abstract
Purpose: To synthesize evidence from systematic reviews on artificial intelligence (AI) applications in prosthodontics and implant dentistry, focusing on clinical applications, AI model performance, and quality of evidence.
Methods: A comprehensive search was conducted in PubMed (MEDLINE), Scopus, Web of Science, Embase, and The Cochrane Library databases, identifying systematic reviews published from 2018 to 2025. Inclusion criteria comprised systematic reviews evaluating AI in prosthodontics or implant dentistry, published in English. Narrative reviews and reviews from other dental specialties were excluded. Two reviewers independently performed study selection and data extraction, and the methodological quality of the included systematic reviews was assessed using A Measurement Tool to Assess Systematic Reviews (AMSTAR-2) tool. This umbrella review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (CRD420251067048).
Results: Eleven systematic reviews were included. AI demonstrated substantial capability in prosthodontics for caries and fracture detection (with an accuracy of ∼82%-89%), automated tooth shade matching, and prosthesis design. In implant dentistry, AI algorithms accurately identified implant types on radiographs (∼95.6% pooled accuracy), optimized implant placement planning, and predicted treatment outcomes with moderate accuracy (62.4%-80.5%). Performance was strongest for radiographic identification and…
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