Faculty of Information Technology, Czech Technical University in Prague, Thakurova 9, Prague 16000, Czech Republic.
Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Vinicna 7, Prague 12843, Czech Republic.
Forensic Sci Int. 2023 Aug;349:111765. doi: 10.1016/j.forsciint.2023.111765. Epub 2023 Jun 15.
This work presents an automated data-mining model for age-at-death estimation based on 3D scans of the auricular surface of the pelvic bone. The study is based on a multi-population sample of 688 individuals (males and females) originating from one Asian and five European identified osteological collections. Our method requires no expert knowledge and achieves similar accuracy compared to traditional subjective methods. Apart from data acquisition, the whole procedure of pre-processing, feature extraction and age estimation is fully automated and implemented as a computer program. This program is a part of a freely available web-based software tool called CoxAGE3D. This software tool is available at https://coxage3d.fit.cvut.cz/ Our age-at-death estimation method is suitable for use on individuals with known/unknown population affinity and provides moderate correlation between the estimated age and actual age (Pearson's correlation coefficient is 0.56), and a mean absolute error of 12.4 years.
这项工作提出了一种基于骨盆耳状面 3D 扫描的年龄估计自动化数据挖掘模型。该研究基于一个多人群样本，包括来自一个亚洲和五个欧洲鉴定骨骼收藏的 688 个人（男性和女性）。我们的方法不需要专业知识，并且与传统的主观方法相比具有相似的准确性。除了数据采集之外，预处理、特征提取和年龄估计的整个过程都是完全自动化的，并实现为一个计算机程序。该程序是一个名为 CoxAGE3D 的免费网络软件工具的一部分。该软件工具可在 https://coxage3d.fit.cvut.cz/ 上获得。我们的年龄估计方法适用于已知/未知人群亲和力的个体，并提供了估计年龄与实际年龄之间的中度相关性（皮尔逊相关系数为 0.56），以及 12.4 年的平均绝对误差。
