Sironi Emanuele, Pinchi Vilma, Taroni Franco
School of Criminal Justice, University of Lausanne, Building Batochime, 1015 Lausanne-Dorigny, Switzerland.
Department of Health Sciences, Section of Forensic Medical Sciences, University of Florence, Largo Brambilla 3, 50134 Florence, Italy.
Forensic Sci Int. 2016 Jan;258:81-7. doi: 10.1016/j.forsciint.2015.11.010. Epub 2015 Nov 27.
In the past few decades, the rise of criminal, civil and asylum cases involving young people lacking valid identification documents has generated an increase in the demand of age estimation. The chronological age or the probability that an individual is older or younger than a given age threshold are generally estimated by means of some statistical methods based on observations performed on specific physical attributes. Among these statistical methods, those developed in the Bayesian framework allow users to provide coherent and transparent assignments which fulfill forensic and medico-legal purposes. The application of the Bayesian approach is facilitated by using probabilistic graphical tools, such as Bayesian networks. The aim of this work is to test the performances of the Bayesian network for age estimation recently presented in scientific literature in classifying individuals as older or younger than 18 years of age. For these exploratory analyses, a sample related to the ossification status of the medial clavicular epiphysis available in scientific literature was used. Results obtained in the classification are promising: in the criminal context, the Bayesian network achieved, on the average, a rate of correct classifications of approximatively 97%, whilst in the civil context, the rate is, on the average, close to the 88%. These results encourage the continuation of the development and the testing of the method in order to support its practical application in casework.
在过去几十年中，涉及缺乏有效身份证件的年轻人的刑事、民事和庇护案件不断增加，这使得年龄估计的需求也随之上升。实际年龄或个人大于或小于给定年龄阈值的概率通常通过基于对特定身体特征的观察的一些统计方法来估计。在这些统计方法中，那些在贝叶斯框架下开发的方法允许用户进行连贯且透明的赋值，以满足法医和法医学目的。使用概率图形工具（如贝叶斯网络）有助于贝叶斯方法的应用。这项工作的目的是测试科学文献中最近提出的用于年龄估计的贝叶斯网络在将个体分类为18岁以上或以下方面的性能。对于这些探索性分析，使用了科学文献中与内侧锁骨骨骺骨化状态相关的样本。分类结果很有前景：在刑事背景下，贝叶斯网络平均实现了约97%的正确分类率，而在民事背景下，平均正确率接近88%。这些结果鼓励继续开发和测试该方法，以支持其在实际案件中的应用。
