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

Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
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

448
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...
448
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

66
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...
66
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

64
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
64
Weighted Mean00:57

Weighted Mean

5.0K
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
5.0K
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

394
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
394

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

Patterns of Antibiotic Utilization and Bacterial Susceptibility of Prenatal Urinary Tract Infections.

Journal of women's health (2002)·2026
Same author

Inference on summaries of a model-agnostic longitudinal variable importance trajectory with application to suicide prevention.

The annals of applied statistics·2026
Same author

Predicting and differentiating accidental and self-harm drug poisonings using health records data.

PLOS mental health·2026
Same author

Incidence and risk factors of <i>C. trachomatis</i>, <i>N. gonorrhoeae</i> and syphilis among a cohort of urban Canadian gay, bisexual and other men who have sex with men, 2017-2023: informing the potential impact of doxycycline prophylaxis.

BMJ open·2026
Same author

Metabolic Dysfunction-Associated Steatotic Liver Disease Is Associated With Impaired Health-Related Quality of Life in People With HIV.

Gastro hep advances·2026
Same author

Preventing Severe Hypoglycemia in Type 2 Diabetes: Randomized Controlled Trial of Proactive Care With Versus Without Psychoeducation.

Journal of general internal medicine·2026
Same journal

Power and sample size calculation of two-sample projection-based testing for sparsely observed functional data.

Stat·2026
Same journal

Bias correction for nonignorable missing counts of areal HIV new diagnosis.

Stat·2025
Same journal

Reaping what you SOW: Guidelines and strategies for writing scopes of work for statistical consulting.

Stat·2025
Same journal

Communication-Efficient Distributed Estimation of Causal Effects With High-Dimensional Data.

Stat·2025
Same journal

Multiple third-variable analysis for competing risk data-With an application to explore racial disparity in breast cancer recurrence.

Stat·2025
Same journal

Reproducible research practices: A tool for effective and efficient leadership in collaborative statistics.

Stat·2024
查看所有相关文章

相关实验视频

Updated: Jun 18, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.4K

不同的私人结果加权学习,以获得最佳的动态治疗方案估计.

Dylan Spicker1, Erica E M Moodie2, Susan M Shortreed3,4

  • 1Department of Mathematics and Statistics, University of New Brunswick (Saint John), NB, Canada.

Stat
|July 29, 2024
PubMed
概括
此摘要是机器生成的。

精准医学使用患者数据进行量身定制的治疗. 一种新的差异化私有结果加权学习 (OWL) 方法在动态处理模式 (DTR) 中保护敏感信息,平衡隐私与准确性.

关键词:
不同的隐私差异 隐私差异动态处理方案 动态处理方案个人待遇规则 个人待遇规则精准医学是一门精准医学.支持矢量机器的支持矢量机器.

更多相关视频

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.2K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

4.5K

相关实验视频

Last Updated: Jun 18, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.4K
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.2K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

4.5K

科学领域:

  • 生物统计学 生物统计学
  • 医疗信息学 医疗信息学
  • 机器学习 机器学习

背景情况:

  • 精准医药使用患者特定数据量身定制治疗方法.
  • 动态治疗方案 (DTRs) 正式化了个性化的纵向护理.
  • 结果加权学习 (OWL) 通过使用支持矢量机器 (SVM) 来从观察数据中估计最佳的DTR.

研究的目的:

  • 用OWL.L.来调查DTR估计中的差异性隐私的整合.
  • 为DTRs开发一个差异化的私有OWL估计器.
  • 量化隐私和准确性之间的权衡在差异性私有DTR估计中.

主要方法:

  • 开发了一个对DTRs的差异性私有OWL估计器.
  • 利用差异性隐私原则,在SVM分类框架内保护个人患者数据.
  • 提供理论分析来量化隐私准确性成本.

主要成果:

  • 该研究引入了第一个对DTRs的差异性私人OWL估计器.
  • 理论结果量化了与实现差异隐私相关的准确性成本.
  • 拟议的方法解决了基于SVM的DTR估计中固有的隐私问题.

结论:

  • 差异性隐私可以有效地集成到OWL中,用于DTR估计.
  • 开发的方法为精准医学提供了一种保护隐私的方法.
  • 未来的工作可以探索在复杂的DTR模型中优化隐私准确性权衡.