ReviewFrontiers in neurology2025
Recent advances and educational strategies in diagnostic imaging for temporomandibular disorders: a narrative literature review.
Review in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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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
5 citing papers in PubMed.
- Decoding adolescent TMJ osteoarthritis with multimodal machine learning.Journal of oral & facial pain and headache · 2026Article
- Recent advances in artificial intelligence-assisted medical imaging education.Frontiers in medicine · 2026Review
- Multicenter evaluation of a digital screening tool for early identification of temporomandibular disorder risk in Colombian and Mexican adults.Frontiers in medicine · 2026Article
- Global research trends in MRI of temporomandibular disorders: a bibliometric study and visualization analysis via CiteSpace.Journal of oral & facial pain and headache · 2025Article
- Quo Vadis Temporomandibular Disorders? By 2050, the Global Prevalence of TMD May Approach 44.Journal of clinical medicine · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Temporomandibular disorders (TMD) are a group of orofacial conditions characterized by pain and dysfunction of the temporomandibular joint (TMJ) and surrounding musculature. Imaging plays a crucial role in diagnosis and treatment planning. However, educational content on TMD imaging in medical and dental curricula has lagged behind recent technological advances. Methods: This review analyzes the current status of TMD imaging education based on a synthesis of literature and educational practices. It highlights discrepancies across institutional curricula and evaluates emerging strategies such as interdisciplinary learning, artificial intelligence (AI)-assisted tools, and simulation-based training. Results: TMD imaging education is found to be inconsistent and underdeveloped globally, with significant variability in curriculum design and limited integration of modern imaging technologies. Current training programs lack standardized guidelines, resulting in knowledge gaps and increased risk of clinical misjudgment. Early findings suggest that AI and simulation tools can enhance educational outcomes. Discussion: To bridge the gap between clinical practice and technology, a standardized, evidence-based educational framework is essential. Future strategies should include interprofessional collaboration, AI-driven diagnostic support, and immersive simulation environments. Implementing these measures will enable clinicians to accurately interpret TMD imaging and improve patient care.
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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.