ReviewCureus2026
Digital Dentistry and Artificial Intelligence: A Systematic Review on Innovations in Diagnosis, Treatment Planning, and Prosthodontics.
Review in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital dentistry has rapidly evolved through the integration of advanced imaging, computer-aided design (CAD) and manufacturing (CAM), and data-driven workflows, creating opportunities for artificial intelligence (AI)-enabled clinical support across multiple dental domains. Although numerous studies have explored AI in isolated diagnostic or restorative applications, a comprehensive synthesis spanning diagnosis, treatment planning, and prosthodontics remains limited, leaving uncertainty regarding the overall scope and maturity of current evidence. This systematic review aimed to consolidate and evaluate published research on AI applications within digital dentistry, with emphasis on data modalities, algorithmic tasks, and reported clinical outcomes. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant search was conducted across PubMed/MEDLINE, Scopus, Web of Science, IEEE Xplore, and Google Scholar for studies published between 2015 and 2025. Eligible peer-reviewed studies reporting quantitative outcomes were systematically screened, extracted, and synthesized descriptively. The review identified a predominance of image-based diagnostic applications, particularly for caries detection and anatomical segmentation, with fewer studies addressing treatment planning and prosthodontic workflows. Deep learning models were most frequently employed, and reported outcomes commonly focused on accuracy, segmentation performance, and spatial agreement. The findings indicate that AI is increasingly embedded within digital dental workflows, primarily as a decision support tool rather than a standalone system. This synthesis clarifies current research trends, highlights the relative maturity of diagnostic applications, and underscores the expanding but uneven integration of artificial intelligence across interconnected stages of digital dentistry, providing a consolidated evidence base to inform clinicians and researchers.
Indexed as
Identifiers
What OpenQuestion holds
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.