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相关实验视频

Updated: Jun 22, 2025

A Morphometric and Cellular Analysis Method for the Murine Mandibular Condyle
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A Morphometric and Cellular Analysis Method for the Murine Mandibular Condyle

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通过使用机器学习算法和人工神经网络对下的形态测量来估计性别.

D Şenol1, F Bodur2, Y Seçgin3

  • 1Department of Anatomy, Düzce University Faculty of Medicine, Düzce, Turkey.

Nigerian journal of clinical practice
|June 29, 2024
PubMed
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性别可以准确地估计使用机器学习分析从下口腔的形态测量. 这项研究突出了下巴在法医和人类学性别确定方面的潜力.

科学领域:

  • 法医人类学 法医人类学
  • 医疗成像医学成像
  • 机器学习 机器学习

背景情况:

  • 从骨遗骸中确定性别在法医和人类学中至关重要.
  • 下是坚固且双形的骨头,因此对此类分析非常有价值.
  • 下舌是下的一个关键的解剖学地标.

研究的目的:

  • 估计性别使用 mandibular lingula 的形态测量测量.
  • 应用机器学习算法和人工神经网络用于性别估计.
  • 为了调查下下肢舌头测量在性别确定中的准确性.

主要方法:

  • 形束计算机断层扫描 (CBCT) 图像获得了下下的图像.
  • 图像被转换成3D格式进行分析.
  • 从3D模型中测量了8个双边人类参数.

主要成果:

  • 机器学习算法在性别估计方面取得了高准确性.
  • 随机森林和高斯的天真贝叶斯算法产生了0.88.8的最高精度.
  • 其他参数的准确率在0.78和0.88.8之间.

结论:

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  • mandibular lingula 形态测量提供了一个非常准确的方法来确定性别.
  • 这些发现支持使用下,特别是舌头,以及骨盆和头骨分析.
  • 这项研究为口腔牙科外科医生,人类学家和法医专家提供了宝贵的解剖学数据,特别是针对土耳其人群.