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相关概念视频

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

60
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
60
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

104
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
104
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

399
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
399

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相关实验视频

Updated: Jun 9, 2025

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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多站点规范模拟的扩散张力图像度量使用等级贝叶斯回归的扩散张力图像度量.

Julio E Villalón-Reina1, Clara A Moreau2, Talia M Nir1

  • 1Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|October 31, 2024
PubMed
概括

层次贝叶斯回归 (HBR) 为多站点脑成像研究提供了数据协调的替代方案. 多项式和b-spline模型使用扩散张力成像 (DTI) 度量有效捕捉白质微观结构的与年龄相关的变化.

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Diffusion Imaging in the Rat Cervical Spinal Cord
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科学领域:

  • 神经成像是一种神经成像.
  • 生物统计学 生物统计学
  • 计算神经科学是一种神经科学.

背景情况:

  • 多站点成像研究提高了统计能力,但需要数据协调.
  • 层次贝叶斯回归 (HBR) 在规范建模中为协调提供了一个替代方案.
  • 扩散张力成像 (DTI) 提供了对白质微观结构的洞察.

研究的目的:

  • 评估HBR对DTI指标在整个生命周期中的多站点规范建模的实用性.
  • 在HBR框架内比较线性,多项式和b-spline模型,用于年龄依赖模型.
  • 证明HBR在检测群体差异中的应用,例如在遗传变异载体中.

主要方法:

  • 使用线性,多项式和b-spline模型应用HBR到横截面DTI数据.
  • 利用了来自8个国际站点的1,300多名年龄在2至80岁的健康受试者的数据.
  • 在白质微观结构的DTI指标中建模了与年龄相关的变化.

主要成果:

  • 与线性模型相比,多项式和b-spline模型在捕获DTI指标年龄依赖性方面表现优越.
  • 该HBR框架成功模拟了DTI指标的规范年龄轨迹.
  • 该方法用于识别遗传副本数变异载体的微观结构差异.

结论:

  • HBR为DTI指标的多站点规范建模提供了一个强大的框架,规避了数据协调的需要.
  • 非线性模型 (多项式,b-spline) 比线性模型更适合捕捉与年龄相关的白质微观结构变化.
  • HBR方法对于检测大脑微观结构中的微妙群体差异非常有价值,模型的复杂性会影响研究结果.