Photograph-Based Skeletal Malocclusion Screening with Geometric Machine Learning: External Validation Across Turkish and Non-European Cohorts

A photograph based screening classifier for skeletal malocclusion maps 100 engineered geometric feature vectors, derived from a side-profile smartphone photograph, to orthodontic class labels, enabling non-invasive triage without radiographic imaging. This study reports external validation across two independent cohorts that contributed no cases to training. Two binary tasks were evaluated; Class III against non-Class III, and Class I against Class II; each with its own development set and model, applied without modification at the default threshold. One external cohort was Turkish, drawn from

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