ArticleEvidence-based dentistry2026
Emerging trends in the early diagnosis of dental caries: a scoping review of artificial intelligence, digital diagnostics, and teledentistry.
Article in Evidence-based dentistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Role of artificial intelligence in teledentistry diagnosis and treatment planning.Bioinformation · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDental caries is the most prevalent chronic, noncommunicable condition affecting individuals of all ages and socio-economic status. The recent technological advancements in artificial intelligence (AI), digital diagnostics, and teledentistry have been genuinely promising in revolutionizing the future of early caries detection and preventive care. However, an integrated understanding of these advancements and their clinical readiness remains limited.
aimTo systematically map and synthesize the current evidence on the use of AI, digital diagnostic technologies, and teledentistry for the early diagnosis in dental caries.
methodThis scoping review followed the Arksey and O'Malley framework and adhered to PRISMA-ScR guidelines. Studies published between 1997 and 2025 were identified through PubMed, Scopus, Web of Science, and manual searches. Articles with AI, digital diagnostic tools, or teledentistry for caries detection were selected, with a specific focus on early caries detection. Data extraction was performed using a standardized charting form and narration across three topics: AI-assisted diagnostics, digital tools, and remote detection through teledentistry.
resultsThirty studies were considered after screening and evaluation of eligibility as they met the selection criteria out of 1000 initial records. The studies included retrospective (n = 10), prospective (n = 7), diagnostic accuracy (n = 6), in-vitro (n = 5), and feasibility studies (n = 2). AI-supported studies showed excellent diagnostic accuracy ranging from well over 90% for the more performing AI to sensitivity and specificity values of 80-95%. However, digital methods, including near-infrared light transillumination, laser fluorescence, photothermal imaging, and ultrasonic technology yielded mixed but positive results in early lesion identification.
conclusionThis scoping review highlights the increasing role of AI, digital diagnostics, and teledentistry in the early detection of dental caries. These technologies augment diagnostic precision, improve preventive care, and provide greater access, particularly for underserved areas. However, regarding real-world validation, standardization and ethical integration remain challenges. Future work needed in clinical trials, data quality, and regulatory harmonization to support safe, effective, and equitable implementation in dental practice.
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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.