ReviewDiagnostics (Basel, Switzerland)2022
Current Applications of Deep Learning and Radiomics on CT and CBCT for Maxillofacial Diseases.
Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 2 of them syntheses that pooled it.
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Who cites it
42 citing papers in PubMed, 2 syntheses or guidelines pooled it, 71 citations in OpenAlex.
- Current evidence of generative artificial intelligence specifically developed for dental and maxillofacial radiology: a systematic review.Dento maxillo facial radiology · 2026Pooled it
- Detection of periodontal bone loss and periodontitis from 2D dental radiographs via machine learning and deep learning: systematic review employing APPRAISE-AI and meta-analysis.Dento maxillo facial radiology · 2025Pooled it
- Whole-axis versus odontoid process CBCT radiomics for forensic sex estimation: a retrospective paired-ROI model-development study.International journal of legal medicine · 2026Article
- Deep learning-enhanced detection of dental restorations and orthodontic appliances in panoramic radiographs using a clinically annotated dataset.Acta odontologica Scandinavica · 2026Article
- AI-Assisted Classification of Mandibular First Molars According to the Presence of an Additional Distal Canal on CBCT Images: Automated CBCT Mandibular Canal Detection.Journal of imaging informatics in medicine · 2026Article
- Radiomics-Based Differential Diagnosis of Radicular Cysts and Apical Granulomas on CBCT Images Using RadC-CNN Architecture.Diagnostics (Basel, Switzerland) · 2026Article
- Artificial Intelligence in Predicting Mortality Risk for Critically Ill Children in Pediatric Intensive Care Units: A Systematic Review.Health science reports · 2026Review
- Radiomics in the Evaluation of Cystic and Neoplastic Lytic Lesions of the Jaws.Diagnostics (Basel, Switzerland) · 2026Article
- CBCT Assessment for Dental Implant Surgery at the Maxilla: A Clinical Update.Diagnostics (Basel, Switzerland) · 2026Review
- How artificial intelligence is reshaping citation impact in oral and maxillofacial radiology journals: an 8-year analysis with editorial and clinical implications (JCR 2017-2024).Frontiers in research metrics and analytics · 2026Article
- [Formula: see text] : explainable attentive transformers for identifying the factors influencing dental visits to enhance dental data completeness.BMC oral health · 2025Article
- Deep learning for imaging diagnosis of jaw cystic lesions and maxillofacial tumors: A narrative review.The Journal of international medical research · 2025Review
- Radiomics-based classification of pediatric dental trauma in periapical radiographs: a preliminary study.BMC medical imaging · 2025Article
- Characteristics, licensing, and ethical considerations of openly accessible oral-maxillofacial imaging datasets: a systematic review.NPJ digital medicine · 2025Article
- Leveraging CRISPR-Cas-Enhanced Isothermal Amplification Tools for Quick Identification of Pathogens Causing Livestock Diseases.Current microbiology · 2025Review
- Computed Tomography in Predicting the Mandibular Involvement by Oral Cancer, a Retrospective Study.Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India · 2025Article
- Feasibility of occlusal plane in predicting the changes in anteroposterior mandibular position: a comprehensive analysis using deep learning-based three-dimensional models.BMC oral health · 2025Article
- Radiographic Evaluation of Implant Stability and Osseointegration in Adult Orthodontic Patients : Radiographic Evaluation of Implant Stability and Osseointegration.Galen medical journal · 2025Review
- Artificial intelligence integrates multi-omics data for precision stratification and drug resistance prediction in breast cancer.Frontiers in oncology · 2025Review
- Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing use of computed tomography (CT) and cone beam computed tomography (CBCT) in oral and maxillofacial imaging has driven the development of deep learning and radiomics applications to assist clinicians in early diagnosis, accurate prognosis prediction, and efficient treatment planning of maxillofacial diseases. This narrative review aimed to provide an up-to-date overview of the current applications of deep learning and radiomics on CT and CBCT for the diagnosis and management of maxillofacial diseases. Based on current evidence, a wide range of deep learning models on CT/CBCT images have been developed for automatic diagnosis, segmentation, and classification of jaw cysts and tumors, cervical lymph node metastasis, salivary gland diseases, temporomandibular (TMJ) disorders, maxillary sinus pathologies, mandibular fractures, and dentomaxillofacial deformities, while CT-/CBCT-derived radiomics applications mainly focused on occult lymph node metastasis in patients with oral cancer, malignant salivary gland tumors, and TMJ osteoarthritis. Most of these models showed high performance, and some of them even outperformed human experts. The models with performance on par with human experts have the potential to serve as clinically practicable tools to achieve the earliest possible diagnosis and treatment, leading to a more precise and personalized approach for the management of maxillofacial diseases. Challenges and issues, including the lack of the generalizability and explainability of deep learning models and the uncertainty in the reproducibility and stability of radiomic features, should be overcome to gain the trust of patients, providers, and healthcare organizers for daily clinical use of these models.
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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.