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CBCT-Based Morphometric Clustering for Orthodontic Diagnostics Using PCA and K-Means: An Explainable AI Workflow

2025-11-11

Abstract excerpt

<title>Abstract</title> <p>Background: Cone-beam computed tomography (CBCT) enables three-dimensional assessment of craniofacial structures; however, translating multiple inter‑correlated measurements into diagnostic insight remains challenging. <h4>Objective:</h4> To present an explainable engineering workflow combining principal component analysis (PCA) and K‑means clustering to identify skeletal Class II pheno...

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Literature Corpus work
262e56c5-942c-5655-a115-f6ef5257ca8f
DOI
10.21203/rs.3.rs-8049618/v1
Open publication

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CBCT-Based Morphometric Clustering for Orthodontic Diagnostics Using PCA and K-Means: An Explainable AI WorkflowDOI 10.21203/rs.3.rs-8049618/v1
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