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Machine learning models for improving the diagnosing efficiency of skeletal class I and III in German orthodontic patients

URN to cite this document:
urn:nbn:de:bvb:355-epub-765772
DOI to cite this document:
10.5283/epub.76577
Paddenberg-Schubert, Eva ; Midlej, Kareem ; Krohn, Sebastian ; Schröder, Agnes ; Awadi, Obaida ; Masarwa, Samir ; Lone, Iqbal M. ; Zohud, Osayd ; Kirschneck, Christian ; Watted, Nezar ; Proff, Peter ; Iraqi, Fuad A.
[img]License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 15 Apr 2025 10:21



Abstract

The precise and efficient diagnosis of an individual’s skeletal class is necessary in orthodontics to ensure correct and stable treatment planning. However, it is difficult to efficiently determine the true skeletal class due to several correlations between various anatomic structures. The primary outcome of this prospective cross-sectional study was developing a machine learning model for ...

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