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The age at death assessment in a multi-ethnic sample of pelvic bones using nature-inspired data mining methods
Authors:Buk Zdenek  Kordik Pavel  Bruzek Jaroslav  Schmitt Aurore  Snorek Miroslav
Institution:Computational Intelligence Group, Department of Computer Science and Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Karlovo náměstí 13, 121 35 Prague, Czech Republic. bukz1@fel.cvut.cz
Abstract:Recently published studies showed that age assessment methods are population specific. Authors analyse the senescence changes in pubic symphysis and sacro-pelvic surface of a pelvic bone using data mining methods. The multi-ethnic data set consists of 956 adult individuals ranging from 19 to 100 years of age derived from 9 different populations with known age and sex. The results show that accurate and reliable age assessment is possible to three age classes (less than 30, 30-60, 60 and more). The study confirms that population specificity of the methods exists and the variable "sex" is not important in age classification.
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