Sex estimation from patellar measurements in a contemporary Italian population: a machine learning approach.

Int J Legal Med

LABANOF (Laboratorio di Antropologia e Odontologia Forense), Department of Biomedical Science for Health, University of Milan, Via Mangiagalli 37, Milan, 20133, Italy.

Published: November 2024

AI Article Synopsis

  • Biological sex estimation in forensic anthropology is examined using the patella, which shows notable sexual dimorphism, making it a valuable bone for this analysis.
  • The study employs 12 machine learning models based on three patellar measurements from 180 skeletons (83 males and 97 females) and 21 forensic cases (13 males and 8 females).
  • The SVM classifier achieved the highest accuracy, with results showing up to 95% accuracy for independent samples, marking the first application of machine learning techniques for patellar measurements in an Italian population.

Article Abstract

Biological sex estimation in forensic anthropology is a crucial topic, and the patella has shown promise in this regard due to its sexual dimorphism. This study uses 12 machine learning models for sex estimation based on three patellar measurements (maximum height, breadth, and thickness). Data was collected from 180 skeletons of a contemporary Italian population (83 males and 97 females) as well as from an independent sample of 21 forensic cases (13 males and 8 females). Statistical analyses indicated that each of the variables exhibited significant sexual dimorphism. To predict biological sex, the classifiers were built using 70% of a reference sample, then tested on the remaining 30% of the original sample and then tested again on the independent sample. The different classifiers generated accuracies varied between 0.85 and 0.91 on the reference sample and between 0.71 and 0.95 for the validation sample. SVM classifier stood out with the highest accuracy and seemed the best model for our study.This study contributes to the growing application of machine learning in forensic anthropology by being the first to apply such techniques to patellar measurements in an Italian population. It aims to enhance the accuracy and efficiency of biological sex estimation from the patella, building on promising results observed with other skeletal elements.

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Source
http://dx.doi.org/10.1007/s00414-024-03359-0DOI Listing

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