Automated classification of skeletal malocclusion in German orthodontic patients

URN to cite this document:: urn:nbn:de:bvb:355-epub-775162
DOI to cite this document:: 10.5283/epub.77516

Paddenberg-Schubert, Eva ; Midlej, Kareem ; Krohn, Sebastian ; Kuchler, Erika ; Watted, Nezar ; Proff, Peter ; Iraqi, Fuad A.

License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 06 Aug 2025 08:15

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Abstract

Objectives: Precisely diagnosing skeletal class is mandatory for correct orthodontic treatment. Artificial intelligence (AI) could increase efficiency during diagnostics and contribute to automated workflows. So far, no AI-driven process can differentiate between skeletal classes I, II, and III in German orthodontic patients. This prospective cross-sectional study aimed to develop machine- and ...