Systematic review of the performance of WebCeph with AI compared to traditional and digital cephalometric methods
Keywords:
cephalometry, diagnosis, computer-assisted, artificial intelligence, orthodontics, pattern recognition automated, WebCephAbstract
Introduction: Cephalometric analysis is a fundamental tool in orthodontics for diagnosis and treatment planning. In recent years, the use of artificial intelligence has made it possible to automate this process. The WebCeph tool stands out for its efficiency and accessibility.
Objective: Analyze the available scientific evidence on the performance of WebCeph as an AI-based tool for cephalometric tracing.
Methods: A systematic review was conducted in accordance with the PRISMA guidelines, with searches in PubMed, Scopus, and Scielo (2020-2025). DeCS/MeSH terms were used in combination with Boolean operators. Original quantitative studies on WebCeph as an AI tool in cephalometry, published in Spanish or English with full text available, were included. Articles without specific mention of WebCeph, reviews, editorials, and abstracts were excluded.
Results: Of the 21 studies included, 9 supported the exclusive use of WebCeph with AI due to its accuracy in simple cases. 10 identified limitations in certain measurements, suggesting clinical supervision. 2 pointed out significant inaccuracies when compared to validated manual or digital methods.
Conclusions: WebCeph proves to be an efficient tool for cephalometric analysis, standing out for its ability to generate tracings in less time than traditional methods. Its performance is reliable in sagittal parameters and in cases with standard anatomical structures. However, in complex measurements or in the presence of severe malocclusions, the accuracy of the software decreases, requiring the intervention of the orthodontist through manual correction of cephalometric points.
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