Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Age Estimation Using Machine Learning Algorithms with Parameters Obtained from X-ray Images of the Calcaneus.

Nigerian journal of clinical practice·2024

Same author

Metaverse in paediatric dentistry.

European archives of paediatric dentistry : official journal of the European Academy of Paediatric Dentistry·2022

Same author

Sex prediction with morphometric measurements of first and fifth metatarsal and phalanx obtained from X-ray images by using machine learning algorithms.

Folia morphologica·2022

Same author

Comparison of anthropometric and conic beam computed tomography measurements of patients with and without difficult intubation risk according to modified mallampati score: New markers for difficult intubation.

Nigerian journal of clinical practice·2021

Same author

Is amygdala size correlated with stress?

Folia morphologica·2020

Same author

Exercise is good also for a healthy hippocampus.

Bratislavske lekarske listy·2019

Search research articles

Related Experiment Video

Updated: Jun 22, 2025

A Morphometric and Cellular Analysis Method for the Murine Mandibular Condyle

A Morphometric and Cellular Analysis Method for the Murine Mandibular Condyle

Published on: January 11, 2018

Gender Estimation from Morphometric Measurements of Mandibular Lingula by Using Machine Learning Algorithms and

D Şenol¹, F Bodur², Y Seçgin³

¹Department of Anatomy, Düzce University Faculty of Medicine, Düzce, Turkey.

Nigerian Journal of Clinical Practice

|June 29, 2024

Summary

This summary is machine-generated.

Gender can be accurately estimated using machine learning analysis of morphometric measurements from the mandibular lingula. This research highlights the potential of the mandible for forensic and anthropological sex determination.

More Related Videos

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible

A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible

Published on: January 28, 2020

Related Experiment Videos

Last Updated: Jun 22, 2025

A Morphometric and Cellular Analysis Method for the Murine Mandibular Condyle

A Morphometric and Cellular Analysis Method for the Murine Mandibular Condyle

Published on: January 11, 2018

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible

A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible

Published on: January 28, 2020

Area of Science:

Forensic Anthropology
Medical Imaging
Machine Learning

Background:

Sex determination from skeletal remains is crucial in forensic medicine and anthropology.
The mandible is a robust and dimorphic bone, making it valuable for such analyses.
The mandibular lingula is a key anatomical landmark on the mandible.

Purpose of the Study:

To estimate gender using morphometric measurements of the mandibular lingula.
To apply machine learning algorithms and artificial neural networks for gender estimation.
To investigate the accuracy of mandibular lingula measurements in sex determination.

Main Methods:

Cone beam computed tomography (CBCT) images of the mandibular lingula were acquired.
Images were converted to 3D format for analysis.
Eight bilateral anthropometric parameters were measured from the 3D models.

Main Results:

Machine learning algorithms achieved high accuracy in gender estimation.
The Random Forest and Gaussian Naive Bayes algorithms yielded the highest accuracy of 0.88.
Other parameters showed accuracy rates between 0.78 and 0.88.

Conclusions:

Mandibular lingula morphometrics offer a highly accurate method for gender determination.
These findings support the use of the mandible, specifically the lingula, alongside pelvis and skull analysis.
The study provides valuable anatomical data for oral-dental surgeons, anthropologists, and forensic experts, particularly for Turkish populations.