Long-Term Predictive Modelling of the Craniofacial Complex Using Machine Learning on 2D Cephalometric Radiographs.

Journal: International dental journal
PMID: 39757033

Abstract

OBJECTIVE: This study aimed to predict long-term growth-related changes in skeletal and dental relationships within the craniofacial complex using machine learning (ML) models.

Authors

  • Michael Myers
    Department of Orthodontics and Oral Facial Genetics, Indiana University School of Dentistry, Indianapolis, Indiana, USA.
  • Michael D Brown
    Indiana University School of Dentistry, Indianapolis, Indiana, USA.
  • Sarkhan Badirli
    Eli Lilly & Company, Indianapolis, Indiana, USA.
  • George J Eckert
    Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA.
  • Diane Helen-Marie Johnson
    Department of Orthodontics and Oral Facial Genetics, Indiana University School of Dentistry, Indianapolis, Indiana, USA.
  • Hakan Turkkahraman
    Department of Orthodontics and Oral Facial Genetics, Indiana University School of Dentistry, 1121 West Michigan Street, 46202, Indianapolis, IN, USA. haturk@iu.edu.

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