ArticleBioinformation2025
Artificial intelligence in the diagnosis of temporomandibular joint disorders using cone-beam computed tomography (CBCT).
Article in Bioinformation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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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Who cites it
2 citing papers in PubMed.
- Temporomandibular Disorders Diagnosis: Current Challenges and the Promising Role of Artificial Intelligence.European journal of dentistry · 2026Article
- Visualization of artificial intelligence applications in oral disease diagnosis: A bibliometric analysis.Digital healthArticle
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Temporomandibular joint disorders represent disorders which hinder the proper functioning of TMJ alongside causing pain-related problems. Therefore, it is of interest to analyse 150 CBCT scans using AI integration methods applied for TMD diagnosis. The AI-generated model displayed 92.4% accurate results and 90.8% sensitivity together with 93.7% specificity at a 0.95 AUC that matched radiologist agreement at κ = 0.89. The availability of AI diagnostics cut down diagnostic assessment time to deliver higher efficiency together with greater consistency. The future application of AI-assisted CBCT analysis appears promising yet needs additional verification steps before it becomes clinically available for broader medical use.
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