SynthesisJournal of prosthodontics : official journal of the American College of Prosthodontists2026
Harnessing AI in prosthodontics and implant dentistry: An umbrella review of systematic evidence.
Synthesis in Journal of prosthodontics : official journal of the American College of Prosthodontists, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Harnessing AI in prosthodontics and implant dentistry: An umbrella review of systematic evidence.Journal of prosthodontics : official journal of the American College of Prosthodontists · 2026Pooled it
- Artificial Intelligence in Implant Dentistry: Clinical Validity, Diagnostic Performance, Surgical Planning, and Medico-Legal Implications-A Narrative Review.Dentistry journal · 2026Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo 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.
methodsA 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).
resultsEleven 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 anatomic segmentation tasks in implant dentistry. It was more modest for preparation margin detection and objective shade matching in prosthodontics, as well as for multivariable prognosis and for detecting maxillary edentulous sites in implant dentistry. Convolutional neural networks (CNNs) consistently outperformed traditional algorithms in image-based tasks. However, AI prediction of long-term outcomes showed moderate performance due to data limitations and biological variability. Overall, although four reviews were rated as high quality, the majority exhibited low or critically low methodological quality, primarily due to a lack of a priori protocol registration and incomplete bias assessment.
conclusionAI applications in prosthodontics and implant dentistry may enhance diagnostic and planning workflows, especially for recognition and segmentation tasks. Nevertheless, most evidence comes from early-stage, retrospective, or highly controlled studies, highlighting the need for prospective clinical validation and higher-quality systematic reviews before routine clinical adoption can be recommended.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.