Use of automated learning techniques for predicting mandibular morphology in skeletal class I, II and III.

Journal: Forensic science international
Published Date: Oct 12, 2017

Abstract

BACKGROUND: The prediction of the mandibular bone morphology in facial reconstruction for forensic purposes is usually performed considering a straight profile corresponding to skeletal class I, with application of linear and parametric analysis which limit the search for relationships between mandibular and craniomaxillary variables.

Authors

  • Tania Camila Niño-Sandoval
    Universidad Nacional de Colombia - Bogotá. Faculty of Dentistry, Oral Health Department. Master of Dentistry. Craniofacial Growth and Development Research Group. Genetics Institute, Cll 53 - Cra. 37 Ed. 426 Of. 213. Bogotá Colombia. Electronic address: kotc2578@gmail.com.
  • Sonia V Guevara Perez
    Universidad Nacional de Colombia - Sede Bogotá. Faculty of Dentistry, Oral Health Department-Orthodontics. Craniofacial Growth and Development Research Group. 11001 Bogotá Colombia. Electronic address: svguevarap@unal.edu.co.
  • Fabio A González
    Machine Learning, Perception and Discovery Lab, Systems and Computer Engineering Department, Universidad Nacional de Colombia, Faculty of Engineering, Cra 30 No 45 03-Ciudad Universitaria, Building 453 Office 114, Bogotá DC, Colombia. Electronic address: fagonzalezo@unal.edu.co.
  • Robinson Andrés Jaque
    Universidad Nacional de Colombia - Bogotá, Faculty of Engineering, Computing Systems and Industrial Engineering Department, MindLab Research Group, Carrera 30 45-03, Bogotá Colombia. Electronic address: rajaquep@unal.edu.co.
  • Clementina Infante-Contreras
    Universidad Nacional de Colombia - Bogotá. Faculty of Dentistry, Oral Health Department. Master of Dentistry. Craniofacial Growth and Development Research Group. Genetics Institute, Cll 53 - Cra. 37 Ed. 426 Of. 213. Bogotá Colombia. Electronic address: ccontrerasi@unal.edu.co.

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