ArticleJournal of clinical medicine2020
Deep Learning for Automated Detection of Cyst and Tumors of the Jaw in Panoramic Radiographs.
Article in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 6 of them syntheses that pooled it.
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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
79 citing papers in PubMed, 6 syntheses or guidelines pooled it, 171 citations in OpenAlex.
- Application, performance and limitations of artificial intelligence for the diagnosis and prediction of oro-facial pain: a systematic review.Frontiers in oral health · 2026Pooled it
- Radiomics-Based Diagnosis in Dentomaxillofacial Radiology: A Systematic Review.Journal of imaging informatics in medicine · 2025Pooled it
- Application and performance of artificial intelligence-based models in the detection, segmentation and classification of periapical lesions: a systematic review.Frontiers in dental medicine · 2025Pooled it
- Development of Artificial Intelligence Models for Tooth Numbering and Detection: A Systematic Review.International dental journal · 2024Pooled it
- Accuracy of machine learning in the diagnosis of odontogenic cysts and tumors: a systematic review and meta-analysis.Oral radiology · 2024Pooled it
- Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review.Pain research & management · 2021Pooled it
- Development of a Preliminary Diagnostic Tool for the Segmentation of Benign Jaw Lesions in CBCT Images Using nnU-Net v2: An Artificial Intelligence-Based Approach.Journal of imaging informatics in medicine · 2026Article
- Role of artificial intelligence in head and neck surgery - A narrative review.Turkish journal of surgery · 2026Article
- Effectiveness of Artificial Intelligence in the Automatic Diagnosis of Lesions Detected in Panoramic Radiographs.Journal of imaging informatics in medicine · 2026Article
- Detection of Jaw Lesions on Panoramic Radiographs Using Deep Learning Method.Journal of imaging informatics in medicine · 2026Article
- Deep Learning-Assisted Localization of Cystic Lesions and Benign Tumors in the Maxillofacial Region Using Panoramic Radiographs: A Preliminary Feasibility Study.Journal of clinical medicine · 2026Article
- Generating Findings for Jaw Cysts in Dental Panoramic Radiographs Using a GPT-Based VLM: A Preliminary Study on Building a Two-Stage Self-Correction Loop with a Structured Output (SLSO) Framework.Diagnostics (Basel, Switzerland) · 2026Article
- Artificial Intelligence in the Diagnosis of Odontogenous Cysts and Ameloblastomas-A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2026Review
- Deep learning-based approach for differential diagnosis of odontogenic cysts from histopathological images.Medicina oral, patologia oral y cirugia bucal · 2026Article
- Segmentation-Guided Preprocessing Improves Deep Learning Diagnostic Accuracy and Confidence of Ameloblastoma and Odontogenic Keratocyst in Cone Beam CT Images-A Preliminary Study.Diagnostics (Basel, Switzerland) · 2026Article
- Evaluation of the effectiveness of artificial intelligence models in radiopaque and radiolucent lesions of the maxillofacial region on panoramic radiographs.Oral radiology · 2026Article
- Deep learning for imaging diagnosis of jaw cystic lesions and maxillofacial tumors: A narrative review.The Journal of international medical research · 2025Review
- A deep learning approach based on YOLO v11 for automatic detection of jaw cysts.BMC oral health · 2025Article
- Evaluation of Caries Detection on Bitewing Radiographs: A Comparative Analysis of the Improved Deep Learning Model and Dentist Performance.Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.] · 2025Article
- Automated detection and classification of osteolytic lesions in panoramic radiographs using CNNs and vision transformers.BMC oral health · 2025Article
19 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 1 institution in 1 country.
Funding
Abstract
Patients with odontogenic cysts and tumors may have to undergo serious surgery unless the lesion is properly detected at the early stage. The purpose of this study is to evaluate the diagnostic performance of the real-time object detecting deep convolutional neural network You Only Look Once (YOLO) v2-a deep learning algorithm that can both detect and classify an object at the same time-on panoramic radiographs. In this study, 1602 lesions on panoramic radiographs taken from 2010 to 2019 at Yonsei University Dental Hospital were selected as a database. Images were classified and labeled into four categories: dentigerous cysts, odontogenic keratocyst, ameloblastoma, and no cyst. Comparative analysis among three groups (YOLO, oral and maxillofacial surgeons, and general practitioners) was done in terms of precision, recall, accuracy, and F1 score. While YOLO ranked highest among the three groups (precision = 0.707, recall = 0.680), the performance differences between the machine and clinicians were statistically insignificant. The results of this study indicate the usefulness of auto-detecting convolutional networks in certain pathology detection and thus morbidity prevention in the field of oral and maxillofacial surgery.
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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.