SynthesisFrontiers in dental medicine2026
Parameter-level comparison of artificial intelligence and manual cephalometric measurements: a systematic review and meta-analysis.
Synthesis in Frontiers in dental medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Authors and funding
11 authors.
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Abstract
Introduction: Prior work has largely focused on landmark-localization error and runtime; whether AI-derived parameter-level measurements differ systematically from those obtained by manual cephalometric analysis remains unclear. Objective: To compare parameter-level cephalometric measurements obtained using AI systems with manual reference methods through a systematic review and meta-analysis; secondarily, to narratively summarize any reported diagnostic metrics (κ/ICC, sensitivity/specificity, AUC) without pooling. Methods: Six databases (PubMed, Scopus, Web of Science, IEEE Xplore, EBSCO, and SciELO) were searched with no time restriction (inception to 20 September 2025) and no language limits; citation chasing was performed (Google Scholar). Eligible studies directly compared AI-based and manual cephalometric tracings. Random-effects meta-analyses were conducted only for parameter-level cephalometric measurements (primary outcomes), using standardized mean differences (Hedges' Results: Twenty-two studies published between 2020 and 2025 were included. AI showed small and generally non-significant differences compared with manual methods across most evaluated parameters, although the certainty of evidence was low to moderate and heterogeneity was considerable for several outcomes. A statistically significant but small advantage was observed for the ANB angle ( Conclusions: AI-assisted cephalometric analysis produces parameter-level measurements comparable to manual tracings for most evaluated parameters; a small statistical difference for ANB was observed without clear clinical relevance. However, the certainty of evidence is limited by heterogeneity, publication bias, and lack of multicenter validation. AI may complement cephalometric workflows and save time, but it requires expert supervision and does not replace comprehensive orthodontic diagnosis or treatment planning. Funding/COI: As declared in the manuscript. Systematic Review Registration: https://doi.org/10.17605/OSF.IO/WKMVD.
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