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使用机器学习算法的年龄估计,参数来自骨的X射线图像.

R Ciftci1, Y Secgin2, Z Oner3

  • 1Department of Anatomy, Faculty of Medicine, Gaziantep Islam Science and Technology University, Gaziantep, Türkiye.

Nigerian journal of clinical practice
|February 26, 2024
PubMed
概括
此摘要是机器生成的。

机器学习模型使用骨X射线测量可以准确估计骨年龄. 额外树木分类器实现了0.85准确度,突出显示了.

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科学领域:

  • 法医科学 法医科学 法医科学
  • 放射学 放射学是一门学科.
  • 生物医学工程 生物医学工程

背景情况:

  • 骨年龄的确定对于法医,外科和科学应用至关重要.
  • 准确的年龄估计有助于法律调查,医学诊断和人类学研究.

研究的目的:

  • 使用机器学习 (ML) 算法,以高准确度和精度估计年龄.
  • 分析来自健康个体骨X射线图像的参数.

主要方法:

  • 对341名年龄在18-65岁之间的人的足部X射线图像进行了回顾性分析.
  • 测量骨参数:最大宽度 (MW),体宽度 (BW),最大长度 (MAXL),最小长度 (MINL),facies articularis cuboidea高度 (FACH),最大高度 (MAXH) 和 tuber calcanei宽度 (TKW).
  • 应用ML模型对使用分组测量 (20-45,46-64,65+岁) 的年龄估计.

主要成果:

  • 额外树分类器算法在年龄估计中实现了0.85的准确性.
  • 其他ML算法的准确率从0.78到0.82.8不等.
  • 根据SHAP分析确定,脚的最大高度 (MAXH) 参数对年龄估计的贡献最高.

结论:

  • 骨提供了准确和精确的年龄估计的可靠基础.
  • 应用于骨测量的ML算法为年龄确定提供了有前途的方法.