ReviewBMC oral health2026
Revolutionizing endodontics: the impact and innovations of artificial intelligence.
Review in BMC oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
- Federated Learning in Endodontics: A Framework for Privacy-Preserving Multicentre Artificial Intelligence.International dental journal · 2026Review
- Beyond Explainability: The Trust Paradox of Conversational Artificial Intelligence in Endodontics.International dental journal · 2026Article
- Should Artificial Intelligence Literacy Be Integrated in Postgraduate Endodontic Programs?International dental journal · 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
6 authors.
Funding
Abstract
backgroundArtificial intelligence (AI) has been increasingly applied in the diagnosis and treatment of endodontic conditions. This narrative review summarizes the current literature on AI applications in endodontics from a clinical workflow perspective, discussing challenges in translating these approaches to practice and highlighting areas where further research is needed to better understand their effectiveness and limitations.
methodsThis narrative review summarizes applications and innovations of AI in endodontics up to July 2025. Relevant literature was identified through searches of PubMed and Web of Science using a combination of MeSH terms and free-text keywords covering areas such as diagnosis, image analysis, treatment planning, and prognosis prediction. Studies were selected for their relevance to clinical or experimental applications, and a few early, foundational studies were also included to provide context and show how AI has developed in this field.
resultsAI, leveraging its efficient image processing and pattern recognition capabilities, has demonstrated considerable advantages in endodontic imaging analysis. Evidence indicates that AI can assist clinicians in disease diagnosis, treatment planning, and prognosis assessment, thereby enhancing the quality of endodontic care across multiple clinical steps. Moreover, applications of AI in root canal anatomy identification, lesion detection, and integration into digital workflows further optimize clinical decision-making and procedural efficiency.
conclusionsDespite its promising potential in endodontics, the routine clinical application of AI remains limited by several factors, including the scarcity of publicly available databases, insufficient interpretability of algorithms, and ethical and privacy concerns. To achieve comprehensive integration of AI into clinical practice, future efforts could focus on multicenter validation studies, data sharing initiatives, development of interpretable AI models, and establishment of ethical and regulatory frameworks through interdisciplinary collaboration.
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.