ReviewThe Japanese dental science review2023
Deep learning and artificial intelligence in dental diagnostic imaging.
Review in The Japanese dental science review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses that pooled it.
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.
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Who cites it
36 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Exploring a decade of deep learning in dentistry: A comprehensive mapping review.Clinical oral investigations · 2025Pooled it
- Deep learning in the diagnosis of maxillary sinus diseases: a systematic review.Dento maxillo facial radiology · 2024Pooled it
- Clinician-accessible automated machine learning in oral healthcare: A systematic review.The Japanese dental science review · 2026Review
- Deep Learning-Based Automated Diagnostic Charting on Panoramic Radiography: Comparison of YOLOv11 and YOLOv12.Odontology · 2026Article
- Patients' Perspectives on Artificial Intelligence and Digital Transformation in Dental Practice: A Cross-Sectional Study from Romania.Dentistry journal · 2026Article
- Deep learning-enhanced detection of dental restorations and orthodontic appliances in panoramic radiographs using a clinically annotated dataset.Acta odontologica Scandinavica · 2026Article
- Deep Learning-Assisted Three-Dimensional Segmentation of Vertebrobasilar Artery Calcification in Cone Beam Computed Tomography.Journal of imaging informatics in medicine · 2026Article
- Exploring the landscape of artificial intelligence in dental and maxillofacial radiology: a bibliometric analysis of studies and trends.Annals of medicine and surgery (2012) · 2026Review
- Influence of Oral and Maxillofacial Radiology Training and Experience on Attitudes Toward Artificial Intelligence in Dentistry: A Cross-Sectional Questionnaire Study.Healthcare (Basel, Switzerland) · 2026Article
- Comparative performance of one-stage and two-stage deep learning models for instance segmentation of overhanging dental restorations on bitewing radiographs.Scientific reports · 2026Article
- Automated Segmentation of Augmented Bone After Transalveolar Sinus Floor Elevation Using Deep Learning.International dental journal · 2026Article
- Multidimensional Evaluation of AI-Generated Patient Information on Cone Beam-Computed Tomography.Journal of imaging informatics in medicine · 2026Article
- Three-dimensional automatic segmentation of root canals with focus on the second mesiobuccal canal using nnU-Netv2 on CBCT images: deep learning approach.BMC oral health · 2026Article
- FDA-Approved AI Solutions in Dental Imaging: A Narrative Review of Applications, Evidence, and Outlook.International dental journal · 2026Review
- [Formula: see text] : explainable attentive transformers for identifying the factors influencing dental visits to enhance dental data completeness.BMC oral health · 2025Article
- Detection accuracy of an AI platform for dental treatment features on panoramic radiographs - tooth- and patient-level analyses.Scientific reports · 2025Article
- Can artificial intelligence optimize treatment planning and outcome prediction in fixed tooth- and implant-supported prosthodontics? A scoping review.BMC oral health · 2025Article
- AI in Dentistry: Innovations, Ethical Considerations, and Integration Barriers.Bioengineering (Basel, Switzerland) · 2025Review
- Embracing Artificial Intelligence in Dental Practice: An Exploratory Study of Romanian Clinicians' Perspectives and Experiences.Dentistry journal · 2025Article
- Radiomics-based classification of pediatric dental trauma in periapical radiographs: a preliminary study.BMC medical imaging · 2025Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The application of artificial intelligence (AI) based on deep learning in dental diagnostic imaging is increasing. Several popular deep learning tasks have been applied to dental diagnostic images. Classification tasks are used to classify images with and without positive abnormal findings or to evaluate the progress of a lesion based on imaging findings. Region (object) detection and segmentation tasks have been used for tooth identification in panoramic radiographs. This technique is useful for automatically creating a patient's dental chart. Deep learning methods can also be used for detecting and evaluating anatomical structures of interest from images. Furthermore, generative AI based on natural language processing can automatically create written reports from the findings of diagnostic imaging.
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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.