通过使用机器算法对第七椎进行人体测量来预测性别的研究
Esra Cetin Unlu1, Zulal Oner2, Serkan Oner3
1Department of Anatomy, Postgraduate Education Institute, Karabük University, Karabük, Türkiye.
概括
通过CT扫描测量C7脊椎 (脊椎突起) 可以预测性别. 机器学习算法达到高达94%的准确性,表明这种非典型的脊椎存在性二态.
科学领域:
- 法医人类学
- 放射学
- 生物识别
背景情况:
- 传统的性别预测依赖于骨盆和骨.
- 在没有其他骨头的情况下,检查脊椎以确定性别.
- 对于C7脊椎 (脊椎突出) 的性别预测尚未进行广泛研究.
研究的目的:
- 使用C7脊椎的计算机断层扫描 (CT) 图像来预测性别.
- 开发C7脊椎分析的自动测量技术.
- 通过机器学习评估C7脊椎参数的潜力.
主要方法:
- 对200名患者 (100名女性,100名男性,20至50岁) 的CT图像进行了回顾性分析.
- 使用专用软件从C7脊椎自动测量16个长度和3个角度参数.
- 应用各种机器学习算法来根据衍生参数预测性别.
主要成果:
- 机器学习模型的准确率高达94%的性别预测.
- 线性差异分析和线性支向量分类的准确度最高,分别为88.94%和88.92%.
- 这项研究表明C7脊椎的参数呈现性二态.
结论:
- C7脊椎 (脊椎突起) 可以可靠地用于性别预测.
- 自动测量和机器学习分析C7脊椎在法医人类学中提供了一个有前途的工具.
- 这种非典型的脊椎表现出显著的双形性,在法医病例中扩大了性别决定的选项.
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