基于大前牙的牙科测量和机器学习算法预测的门尺寸的性别估计
Kale Taib Karim1, Dler Abdulrahman Mohammad1, Mohammed Taha Ahmed Baban2
1Basic Science Department, College of Dentistry, University of Sulaimani, Sulaymaniyah, Iraq.
Journal of forensic sciences
|February 9, 2026
概括
使用牙科测量的法医性别估计通过3D扫描和机器学习得到了增强. 这种方法可以准确地从前牙上部的尺寸来预测性别,有助于识别人类遗骸.
科学领域:
- 法医人类学 法医人类学
- 牙科法医医学 牙科法医医学
- 机器学习应用 机器学习应用
背景情况:
- 准确的性别估计对于识别未知的人类遗骸至关重要,减少了50%的潜在匹配.
- 人类牙对于性别估计是有价值的,因为它们的耐用性和性二态.
- 内口扫描仪和机器学习提供了高效和准确的法医调查工具.
研究的目的:
- 整合口腔内扫描和机器学习,以从牙和大门的测量来估计性别.
- 评估机器学习模型在预测性别时的准确性,使用前上牙的线性测量.
主要方法:
- 使用3D Slicer软件从200个个体 (100名男性,100名女性) 的数字印记中获得了前牙和门尺寸的线性测量.
- 分析了使用六种机器学习模型预测性别的测量结果.
- 使用嵌套交叉验证进行准确度估计.
主要成果:
- 测量了右和左的宫到尖的测量结果显示,分辨能力最高 (AUC分别为0.968和0.947).
- 支持向量分类器模型实现了最高的平均预测准确率94.5%.
- 开发的方法表明,对准确的性别估计有很大的潜力.
结论:
- 3D口腔内扫描和机器学习的整合为法医性别估计提供了一个高度准确的方法.
- 牙和大门的测量,特别是狗的尺寸,是性别的有效预测.
- 建议使用更大,更多样化的样本进行进一步验证,以提高概括性.
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