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Updated: Jul 5, 2025

Combining Multiple Data Acquisition Systems to Study Corticospinal Output and Multi-segment Biomechanics
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Published on: January 9, 2016

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同时对MRS数据进行多过渡线性组合建模改进了不确定性估计

Helge J Zöllner1,2, Christopher Davies-Jenkins1,2, Dunja Simicic1,2

  • 1Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.

bioRxiv : the preprint server for biology
|January 23, 2024
PubMed
概括

在磁共振光谱学 (MRS) 中的二维 (2D) 多瞬态建模与传统1D建模的性能相匹配. 这项研究验证了2D建模,以在动态MRS数据中准确估计代谢物.

关键词:
动态的MRS可以使用.动态建模的动态建模磁共振光谱学 磁共振光谱学

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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.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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