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在现代希腊样本中测试DRNNAGE软件对年龄估计的准确性

Leuteris Rizos¹, Nefeli Garoufi¹, Eustratios Valakos¹

¹Department of Animal and Human Physiology, Faculty of Biology, School of Sciences, National and Kapodistrian University of Athens, Panepistimiopolis, 157 01, Athens, GR, Greece.

International journal of legal medicine

|November 24, 2023

概括

法医人类学法医人类学.

科学领域:

法医人类学法医人类学.
生物考古学的生物考古学
人类骨生物学人类骨生物学

背景情况:

从骨遗骸中估计死亡时的年龄对于法医人类学中的生物学分析至关重要.
成人骨年龄估计面临着由于生物变异和方法限制的挑战.
提出了一种新的机器学习方法 (DRNNAGE) 来估计骨年龄.

研究的目的:

在现代希腊骨样本上验证DRNNAGE软件及其基础方法.
在不同的人口群体中评估拟议的年龄估计方法的可重复性,可重复性和准确性.
在DRNNAGE模型中评估个体解剖区域和组合特征的性能.

主要方法:

该DRNNAGE软件应用于一个记录的希腊骨样本 (n=219,年龄19-99).
对于选定的骨架变量,计算了观察者内部和观察者间的误差.
对于聚合和分层 (性别,年龄>50) 样本,评估了DRNNAGE的准确性,分析了个别地区和综合数据.

主要成果:

一些变量表现出低的重复性和可重复性,需要谨慎的应用.
在50岁以上的个体中,DRNNAGE表现出很高的准确性,但在年轻人中表现不佳.
部部分析显示,在所有年龄组均有一致的准确性,在年轻人中表现优于其他区域.

结论:

该研究强调了在法医人类学中对年龄估计方法进行交叉验证的必要性.
特定人口的方法对于可靠的骨死亡年龄估计至关重要.
虽然有希望,但DRNNAGE方法需要进一步改进,特别是对于年轻的成年人年龄段.

关键词:

死亡时的年龄估计.软件是 DRNNAGE 软件.希腊的样本来自希腊.验证验证验证验证

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