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. 2024 Dec 10;14(24):2773.
doi: 10.3390/diagnostics14242773.

Sex Estimation Through Orbital Measurements: A Machine Learning Approach for Forensic Science

George Triantafyllou  1 , George G Botis  1   2 , Maria Piagkou  1 , Konstantinos Papanastasiou  2 , George Tsakotos  1 , Ioannis Paschopoulos  1 , George K Matsopoulos  2 , Stavroula Papadodima  3
Affiliations

Sex Estimation Through Orbital Measurements: A Machine Learning Approach for Forensic Science

George Triantafyllou et al. Diagnostics (Basel). .

Abstract

Background: Sex estimation has been extensively investigated due to its importance for forensic science. Several anatomical structures of the human body have been used for this process. The human skull has important landmarks that can serve as reliable sex estimation predictors.

Methods: In this study, orbital measurements from 92 dried skulls, comprising 35 males and 57 females, were utilized to develop a machine-learning-based classifier for sex estimation with potential applications in forensic science. The parameters evaluated included optic foramen height (OFH), optic foramen width (OFW), optic canal height (OCH), optic canal width (OCW), intraorbital distance (IOD), extraorbital distance (EOD), orbit height (OH), and orbit width (OW).

Results: A Random Forest classifier was employed to analyze the data, achieving an overall test accuracy of 0.68. The model demonstrated a precision of 0.65, indicating a moderate level of false positives. The recall was 0.70, reflecting that 70% of the positive cases were correctly identified. The F1 score was calculated at 0.675, suggesting a balanced performance between precision and recall. The area under the curve (ROC AUC) score was also 0.72, indicating that the model can distinguish between classes. The most important features in the best subset were OW (0.2429), IOD (0.2059), EOD (0.1927), OFH (0.1798), and OFW (0.1787), highlighting their significant contributions to the model's predictions.

Conclusions: These findings suggest that orbital measurements could potentially serve as reliable predictors for automated sex estimation, contributing to advancements in forensic identification techniques.

Keywords: anatomy; forensic science; machine learning; optic canal; optic foramen; orbit; orbital measurements; sex estimation.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
The orbital measurements of the current study. (A) Orbit height (OH), orbit width (OW), infraorbital distance (IOD), extraorbital distance (EOD); (B) optic canal (OC), (C) and optic foramen (OF).
Figure 2
Figure 2
Scatter plots between features and bar plots of their frequencies. Relations of proportionality are noticeable (blue: female; orange: male).
See this image and copyright information in PMC

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