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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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使用功能线性模型与林马校正的非特异性部疼痛评估.

Elisa Aragón-Basanta1, Guillermo Ayala2, Álvaro Page3

  • 1Instituto Universitario de Ingeniería Mecánica y Biomecánica, Universitat Politècnica de València, Camino de Vera s/n, Valencia, 46022, Spain. mearba@doctor.upv.es.

Medical & biological engineering & computing
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概括
此摘要是机器生成的。

在非特异性部疼痛患者中,部残疾和年龄显著影响部运动速度和加速. 角曲线没有受到显著的影响,这突显了分析速度和加速数据的重要性.

关键词:
本杰明尼-霍赫伯格纠正功能数据分析的功能数据分析.这里是Lima Limma.多重线性回归的多重线性回归.部残疾指数 部残疾指数

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科学领域:

  • 生物力学 生物力学
  • 临床生物力学 临床生物力学
  • 肌肉骨研究 研究

背景情况:

  • 不特定的部疼痛很普遍,影响日常功能.
  • 了解部动力学对于评估残疾至关重要.
  • 现有的动力学分析可能无法完全捕捉部疼痛的细微差别.

研究的目的:

  • 分析部残疾和部曲-延伸动力学之间的关系.
  • 评估部残疾指数 (NDI),年龄,性别和部长度对运动参数的影响.
  • 为了比较经典回归与经验贝叶斯方法的动力学分析.

主要方法:

  • 在部运动期间的角度,速度和加速曲线的功能分析.
  • 回归模型,包括经典和limma (微阵列数据的线性模型) 方法.
  • 使用Benjaminini-Hochberg方法调整p值以控制错误发现率 (FDR).

主要成果:

  • 在原始和调整的p值之间观察到显著差异,表明未经调整的分析中存在虚假发现.
  • 在FDR调整后,子长度没有显著影响速度或加速度曲线.
  • 部残疾指数 (NDI) 和年龄显著影响了速度和加速曲线,但不是角曲线.

结论:

  • 调整后的p值显示,NDI和年龄是部运动速度和加速的关键预测因素.
  • 只有角动力学曲线是不够的;速度和加速数据提供了互补的见解.
  • 对于非特异性部疼痛,在部动力学研究中应同时分析速度和加速度曲线.