Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Machine Learning Models for Prediction of Gender Based on Lumbar Vertebral Morphometry

Madalina Maria Diac
ORCID logo ,
Gina Madalina Toma
* ,
Simona Irina Damian
* ,
Marin Fotache
,
Nicolai Romanov
,
Daniel Tabian
ORCID logo ,
Gabriela Sechel
,
Andrei Scripcaru
,
Monica Hancianu
,
Diana Bulgaru Iliescu
Version 1 : Received: 2 November 2023 / Approved: 2 November 2023 / Online: 2 November 2023 (10:40:25 CET)

A peer-reviewed article of this Preprint also exists.

Diac, M.M.; Toma, G.M.; Damian, S.I.; Fotache, M.; Romanov, N.; Tabian, D.; Sechel, G.; Scripcaru, A.; Hancianu, M.; Iliescu, D.B. Machine Learning Models for Prediction of Sex Based on Lumbar Vertebral Morphometry. Diagnostics 2023, 13, 3630. Diac, M.M.; Toma, G.M.; Damian, S.I.; Fotache, M.; Romanov, N.; Tabian, D.; Sechel, G.; Scripcaru, A.; Hancianu, M.; Iliescu, D.B. Machine Learning Models for Prediction of Sex Based on Lumbar Vertebral Morphometry. Diagnostics 2023, 13, 3630.

Abstract

Identifying skeletal remains has been and will remain a challenge for forensic doctors and forensic anthropologists, especially in disasters with multiple victims or skeletal remains in an advanced stage of decomposition. This study proposes a machine learning method to determine gender starting from morphometric analysis of L1-L5 lumbar vertebrae in a modern Romanian population. The purpose of the present study was to observe whether by using the ML method there is a good predictability of gender in forensic identification based on parameters obtained from the metric analysis of the lumbar spine specific to the Romanian population. This paper offers two models of ML, RF and XGB, each with its own characteristics, and presenting different performance, random forest having the best. For both, we used two metrics (accuracy and roc_auc), the latter being the most used to highlight model performance. The L1-L5 lumbar vertebrae exhibit sexual dimorphism and can be used in gender estimation. Machine learning is more accurate in determining gender than discriminatory function analysis.

Keywords

forensic identification, machine learning, gender identification, lumbar vertebral column

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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