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用贝叶斯推断和主要成分分析从阴茎耳膜表面估计年龄:在印度人口中进行基于CT的研究
Varsha Warrier1, Rutwik Shedge2, Pawan Kumar Garg3
1Department of Forensic Medicine and Toxicology, All India Institute of Medical Sciences, Jodhpur, 342005, India. warrier_varsha@yahoo.co.in.
Forensic science, medicine, and pathology
|June 5, 2023
概括
使用阴茎的耳膜表面估计年龄的巴克贝里-钱伯莱恩方法适用于印度人口. 基于CT的分析表明,巨性在年龄估计中产生了最高的准确性.
科学领域:
- 法医人类学 法医人类学
- 放射学 放射学是一门学科.
- 人类识别 人类识别
背景情况:
- 年龄估计对于人类识别至关重要.
- 阴茎的耳膜表面是衰老的可靠骨指标,特别是在老年人中.
- 巴克贝里-钱伯莱恩方法提供了一个客观的,基于组件的方法来估计耳朵年龄.
研究的目的:
- 评估巴克贝里-钱伯莱恩耳部年龄估计方法在印度人口中的适用性.
- 用计算机断层扫描 (CT) 来评估耳朵表面与年龄相关的变化.
- 为了比较个体形态特征的准确性,并开发一个总结年龄模型.
主要方法:
- 对435名印度参与者的CT扫描分析了与年龄相关的耳部变化.
- 评估了三种巴克贝里-钱伯莱恩形态特征 (巨孔性,横向组织,顶峰变化).
- 贝叶斯推论和过渡分析用于从个体特征中估计年龄,并开发多变量总结年龄模型.
主要成果:
- 宏透度显示了最高的准确性 (98.64%),误差率为12.99年.
- 横向组织和顶点变化的准确率分别为91.67%和94.84%.
- 综合所有特征的综合年龄模型将不准确率降低到8.52岁.
结论:
- 巴克贝里-钱伯莱恩方法,特别是宏性,是有效的年龄估计在印度人口通过CT扫描.
- 贝叶斯分析从个体特征提供可靠的年龄估计.
- 多变量总结年龄模型为年龄估计提供了更好的准确性和可靠性.
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