ArticleAnnals of medicine and surgery (2012)2026
AI in endodontics: enhancing precision, efficiency, and personalized care.
Article in Annals of medicine and surgery (2012), 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) is shifting oral health care from a hardware-centric to a software-centric approach, with the potential to solve problems similarly to humans. It is transforming endodontics by enhancing diagnostic accuracy, improving treatment planning, increasing clinical efficiency, and supporting personalized care. This review explores AI applications in endodontics, including working length determination, periapical and caries detection, complex root anatomy segmentation, vertical root fracture identification, and surgical planning. AI models such as convolutional neural networks and artificial neural networks demonstrate high accuracy in interpreting cone-beam computed tomography and radiographic data. Benefits include improved workflow efficiency, reduced misdiagnoses, and individualized treatment strategies. However, challenges persist, such as limited high-quality datasets, regulatory gaps, and ethical considerations. Future directions emphasize technological advancements, collaborative AI-clinician integration, and AI-driven education and training tools. AI stands as a transformative force in endodontics, requiring responsible implementation and continued research to optimize its impact on patient care and clinical 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.