ReviewComputational and mathematical methods in medicine2023
Evaluation of the Diagnostic and Prognostic Accuracy of Artificial Intelligence in Endodontic Dentistry: A Comprehensive Review of Literature.
Review in Computational and mathematical methods in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 4 of them syntheses 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
44 citing papers in PubMed, 4 syntheses or guidelines pooled it, 77 citations in OpenAlex.
- American Dental Association and American Academy of Oral and Maxillofacial Radiology patient selection for dental radiography and cone-beam computed tomography: Clinical recommendations.Oral surgery, oral medicine, oral pathology and oral radiology · 2026Guideline
- American Dental Association and American Academy of Oral and Maxillofacial Radiology patient selection for dental radiography and cone-beam computed tomography: Clinical recommendations.Journal of the American Dental Association (1939) · 2026Guideline
- Applications of artificial intelligence in endodontic education: a systematic review.Frontiers in dental medicine · 2026Pooled it
- Artificial Intelligence in Dental Caries Diagnosis and Detection: An Umbrella Review.Clinical and experimental dental research · 2024Pooled it
- Accuracy of large language models in the Turkish dental specialization examination (DUS): a multidimensional evaluation across disciplines and question formats.BMC oral health · 2026Article
- Diagnostic Accuracy of Artificial Intelligence Models for Detecting Odontogenic Keratocytes on CBCT Imaging: A Systematic Review and Meta-Analysis.Health science reports · 2026Review
- Quality, completeness, readability, and response time of AI chatbots in the management of deep caries and pulp exposure: a bilingual comparative study.BMC oral health · 2026Article
- Emerging Artificial Intelligence Technologies for Evaluation of Dental Composite Restorations: A Scoping Review.European journal of dentistry · 2026Article
- Large language models and generative artificial intelligence in endodontics: a scoping review.Odontology · 2026Review
- Evaluation of the performance of ChatGPT-4 and ChatGPT-4o as a learning tool in endodontics.International endodontic journal · 2026Article
- Article
- When Lie Groups Meet Hyperspectral Images: Equivariant Manifold Network for Few-Shot HSI Classification.Sensors (Basel, Switzerland) · 2026Article
- Impacts of artificial intelligence on computed tomography in endodontics: an integrative review.BMC oral health · 2026Review
- Assessing the Role of Artificial Intelligence in Caries Detection and Clinical Decision-Making: A Scoping Review.Caries research · 2026Review
- Artificial intelligence chatbots versus dentists: a comparative knowledge assessment on traumatic dental injury management.BMC oral health · 2026Article
- Developing an AI-powered tool for radiographic feedback on working length determination in pre-clinical endodontic training.Frontiers in dental medicine · 2026Article
- The Leeuwenhoek paradox in dental artificial intelligence: A narrative review of artificial intelligence-detected subclinical periapical changes and human-labeled false positives.Journal of dental sciences · 2026Review
- Error-Tolerant Multimodal Vision-Language Models for Endodontic Triaging: A Cross-Sectional Study.International journal of dentistry · 2026Article
- Comparison of clinical outcomes following periapical surgery in endodontics versus extraction with implant placement.Bioinformation · 2026Article
- Accuracy and response repeatability of three large language models on undergraduate operative dentistry multiple-choice questions.Frontiers in dental medicine · 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
8 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: This comprehensive review is aimed at evaluating the diagnostic and prognostic accuracy of artificial intelligence in endodontic dentistry. Introduction: Artificial intelligence (AI) is a relatively new technology that has widespread use in dentistry. The AI technologies have primarily been used in dentistry to diagnose dental diseases, plan treatment, make clinical decisions, and predict the prognosis. AI models like convolutional neural networks (CNN) and artificial neural networks (ANN) have been used in endodontics to study root canal system anatomy, determine working length measurements, detect periapical lesions and root fractures, predict the success of retreatment procedures, and predict the viability of dental pulp stem cells. Results: The preliminary search yielded 2560 articles relevant enough to the paper's purpose. A total of 88 articles met the eligibility criteria. The majority of research on AI application in endodontics has concentrated on tracing apical foramen, verifying the working length, projection of periapical pathologies, root morphologies, and retreatment predictions and discovering the vertical root fractures. Conclusion: In endodontics, AI displayed accuracy in terms of diagnostic and prognostic evaluations. The use of AI can help enhance the treatment plan, which in turn can lead to an increase in the success rate of endodontic treatment outcomes. The AI is used extensively in endodontics and could help in clinical applications, such as detecting root fractures, periapical pathologies, determining working length, tracing apical foramen, the morphology of root, and disease prediction.
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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.