Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

69
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...
69
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

127
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
127
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

97
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
97
Time-Series Graph00:54

Time-Series Graph

4.4K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
4.4K
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

62
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
62
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

682
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
682

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

The discharge process for a child with complex healthcare needs dependent on respiratory technology: A scoping review protocol.

PloS one·2026
Same author

Enhancing infant pain assessment and treatment: investigating barriers, facilitators, and implementation outcomes with the ImPaC Resource.

Implementation science communications·2026
Same author

Learning to forget: deimplementation and the science of sustainability in healthcare.

BMJ quality & safety·2026
Same author

A Proposed Feasibility Process: Lessons Learned from the Precision MS Project.

Studies in health technology and informatics·2025
Same author

If it wasn't for us, there would be no data: stakeholders' perspectives on patient involvement in the use of health data in Ireland.

Research involvement and engagement·2025
Same author

Data Mapping Challenges in Reproducibility of Machine Learning for Acute Kidney Injury Prediction.

Studies in health technology and informatics·2025
Same journal

Understanding the Interaction Between Infant Feeding and Maternal Mental Health and Well-Being in Women who Experience Psychological Birth Trauma: A Scoping Review Protocol.

HRB open research·2026
Same journal

The Management of Acne in General Practice using Isotretinoin: A Scoping Review Protocol.

HRB open research·2026
Same journal

Conceptualising doctors' and nurses' experience of formal and informal solidarity: A Meta-Ethnography Protocol.

HRB open research·2026
Same journal

CP-EXCEL:  A feasibility randomised controlled trial of an online exercise programme for adults with cerebral palsy.

HRB open research·2026
Same journal

Interventions to improve sexual health among the homeless community: a realist review protocol.

HRB open research·2026
Same journal

Quantifying the carbon footprint of clinical research activities - measurement tools and methods: a scoping review protocol.

HRB open research·2026
查看所有相关文章

相关实验视频

Updated: Jul 1, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.6K

在知识图中建模时间数据:系统审查协议.

Sepideh Hooshafza1,2, Fabrizio Orlandi2, Rachel Flynn1

  • 1Health Information and Quality Authority (HIQA), Cork, Ireland.

HRB open research
|March 4, 2024
PubMed
概括
此摘要是机器生成的。

本系统审查协议概述了在知识图中对时间数据建模的研究. 调查结果将为医疗保健数据管理和分析快速变化的患者信息提供信息.

关键词:
知识图表知识图表资源描述框架 资源描述框架时间数据 时间数据

更多相关视频

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

5.9K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

5.6K

相关实验视频

Last Updated: Jul 1, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.6K
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

5.9K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

5.6K

科学领域:

  • 计算机科学 计算机科学
  • 信息科学 信息科学 信息科学
  • 医疗保健信息学 医疗保健信息学

背景情况:

  • 高质量的医疗保健数据至关重要,但由于高维度和不规则性而面临挑战.
  • 知识图为数据表示提供了一个有前途的方法,但它们对于医疗数据,特别是时间数据的适用性尚未得到充分探索.
  • 管理快速变化的患者数据是一个重大挑战,因为传统模型往往无法考虑时间方面的因素.

研究的目的:

  • 在知识图中概述了一个跨学科系统审查的时间数据建模的协议.
  • 在知识图中调查时间数据建模中现有的方法,应用和挑战.
  • 为有效的医疗数据管理提供知识图的应用提供信息.

主要方法:

  • 综述的重点是研究问题:"在资源描述框架 (RDF) 基础上的知识图中建模时间数据的现有方法是什么?"
  • 两个子问题将评估应用程序和挑战.
  • 搜索将在ACM数字图书馆,IEEE Xplore和Scopus中进行,仅限于基于RDF的知识图的同行评审文献. 将进行叙事合成.

主要成果:

  • 系统性审查将识别和综合当前在基于RDF的知识图中建模时间数据的方法.
  • 它将突出使用时间知识图的关键应用.
  • 将阐明与知识图中的时间数据建模相关的挑战.

结论:

  • 这些发现将为数据工程师在使用时间数据模型来表示和分析数据方面提供宝贵的见解.
  • 结果将适用于医疗保健领域,解决管理动态患者数据的挑战.
  • 这一审查将促进采用知识图表,以改善医疗数据管理和分析.