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Diagnostic Accuracy of Auricular Morphometry in Sex Estimation: A Logistic Regression Model with ROC-Based
Serdar Babacan1, Güven Özkaya2
1Department of Anatomy, Faculty of Medicine, Bursa Uludağ University, 16059 Bursa, Türkiye.
Diagnostics (Basel, Switzerland)
|June 26, 2026
Summary
Ear measurements can accurately estimate biological sex. This study developed a logistic regression model using auricular morphometrics, achieving high accuracy for sex determination in forensic and clinical applications.
Area of Science:
- Forensic Anthropology
- Biometrics
- Human Anatomy
Background:
- Anthropometric measurements are crucial for clinical practice and forensic identification.
- The human ear's unique morphology makes it valuable for biometrics.
- This study investigates ear measurements for biological sex estimation.
Purpose of the Study:
- To estimate biological sex using auricular morphometric measurements.
- To develop and validate a logistic regression model for sex estimation.
- To assess the model's performance using ROC analysis.
Main Methods:
- A cross-sectional study of 120 adults (60 males, 60 females).
- Analysis of 22 linear and 6 angular ear measurements from digital photographs using ImageJ.
- Development of a logistic regression model with LASSO for variable selection.
Main Results:
- Significant sexual dimorphism observed in most linear and angular ear measurements.
- Auricular width (A2) and width at the tragus (A3) were strong indicators of sex.
- A 5-predictor model achieved an AUC of 0.980, demonstrating high discriminative performance.
Conclusions:
- Auricular morphometry is an effective method for biological sex estimation.
- Significant sexual dimorphism exists in external ear dimensions.
- The developed model can serve as a reference for future biometric studies.
