ArticleDento maxillo facial radiology2024
Skeletal facial asymmetry: reliability of manual and artificial intelligence-driven analysis.
Article in Dento maxillo facial radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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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
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Automated assessment of 3D facial asymmetry: a systematic review.European journal of orthodontics · 2026Pooled it
- Artificial intelligence in orthodontics: clinical maturity, evidence gaps, and emerging applications-a narrative review.The Saudi dental journal · 2026Review
- Reliability of AI-Automated and Semiautomated Upper Airway Volume Segmentation.Diagnostics (Basel, Switzerland) · 2026Article
- An Overview of the Currently Used Congenital Auricular Anomalies (CAA) Classifications for Surgical Reconstruction: A Scoping Review.The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association · 2026Article
- Applications of artificial intelligence in diagnosis and treatment planning of orthodontics: a narrative review.The Saudi dental journal · 2025Review
- Review
- Changes of temporomandibular joint space volume during 1 year after transoral vertical ramus osteotomy in patients with mandibular asymmetry.Scientific reports · 2025Article
- Artificial Intelligence-Assisted Segmentation of a Falx Cerebri Calcification on Cone-Beam Computed Tomography: A Case Report.Medicina (Kaunas, Lithuania) · 2024Article
- Comparison of Three Commercially Available, AI-Driven Cephalometric Analysis Tools in Orthodontics.Journal of clinical medicine · 2024Article
- Reliability of the AI-Assisted Assessment of the Proximity of the Root Apices to Mandibular Canal.Journal of clinical medicine · 2024Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo compare artificial intelligence (AI)-driven web-based platform and manual measurements for analysing facial asymmetry in craniofacial CT examinations.
methodsThe study included 95 craniofacial CT scans from patients aged 18-30 years. The degree of asymmetry was measured based on AI platform-predefined anatomical landmarks: sella (S), condylion (Co), anterior nasal spine (ANS), and menton (Me). The concordance between the results of automatic asymmetry reports and manual linear 3D measurements was calculated. The asymmetry rate (AR) indicator was determined for both automatic and manual measurements, and the concordance between them was calculated. The repeatability of manual measurements in 20 randomly selected subjects was assessed. The concordance of measurements of quantitative variables was assessed with interclass correlation coefficient (ICC) according to the Shrout and Fleiss classification.
resultsErroneous AI tracings were found in 16.8% of cases, reducing the analysed cases to 79. The agreement between automatic and manual asymmetry measurements was very low (ICC < 0.3). A lack of agreement between AI and manual AR analysis (ICC type 3 = 0) was found. The repeatability of manual measurements and AR calculations showed excellent correlation (ICC type 2 > 0.947).
conclusionsThe results indicate that the rate of tracing errors and lack of agreement with manual AR analysis make it impossible to use the tested AI platform to assess the degree of facial asymmetry.
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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.