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

Guidelines for Writing Outcome01:11

Guidelines for Writing Outcome

2.7K
When developing expected outcomes for a patient care plan, the nurse should adhere to the following recommendations:
Patient outcomes reflect the patient's response to the goal rather than what the nurse aims to achieve. Terminology should be observable and measurable to avoid the reader's interpretation. The desired outcome should be realistic and achievable in the designated care timeframe. Expected outcomes should align with adjunctive therapies. The outcome should enhance care...
2.7K
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

4.9K
Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
4.9K
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

559
The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic...
559
Secondary Healthcare System01:11

Secondary Healthcare System

1.4K
Secondary healthcare is offered by a specialist, generally in hospitals or clinics for patients referred by primary healthcare providers. It occurs when a person has an illness or injury that requires specific medical care. Secondary care is often referred to as acute care. Secondary care can range from uncomplicated care to repair a minor laceration or treat a strep throat infection to more complicated emergent care, such as treating a head injury sustained in an automobile accident. Whatever...
1.4K
Crossover Experiments01:16

Crossover Experiments

2.7K
Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
2.7K
Tertiary Healthcare System01:21

Tertiary Healthcare System

1.7K
Specialized care provided over an extended period is called tertiary care. Usually, a primary or secondary care physician will refer a patient to tertiary care. A patient's maximum physical and mental function is restored in tertiary care, which is caused due to the impact of a chronic illness or condition. Tertiary care aims to achieve the highest level of functioning possible while managing chronic illness. For example, a patient who falls and fractures their hip will need secondary care...
1.7K

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

Integrative learning of individualized treatment rules from multiple studies with partially overlapping treatments.

Biometrics·2026
Same author

Reproducible workflow for online artificial intelligence in digital health.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2026
Same author

SigmaScheduling: Uncertainty-Informed Scheduling of Decision Points for Intelligent Mobile Health Interventions.

... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks·2026
Same author

SEMIPARAMETRIC ANALYSIS OF INTERVAL-CENSORED DATA SUBJECT TO INACCURATE DIAGNOSES WITH A TERMINAL EVENT.

The annals of applied statistics·2026
Same author

DYNAMIC CLASSIFICATION OF LATENT DISEASE PROGRESSION WITH AUXILIARY SURROGATE LABELS.

The annals of applied statistics·2026
Same author

Asymptotic Inference for Multi-Stage Stationary Treatment Policy with Variable Selection.

Journal of machine learning research : JMLR·2026

相关实验视频

Updated: Jun 11, 2025

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

使用二次结果融合个性化治疗规则.

Daiqi Gao1, Yuanjia Wang2, Donglin Zeng3

  • 1Harvard University.

Proceedings of machine learning research
|October 7, 2024
PubMed
概括

这项研究引入了一种创建个性化治疗规则 (ITR) 的新方法,可以优化主要结果,同时最大限度地减少对次要结果的伤害. 该方法通过同时考虑多个健康目标来增强治疗决策.

科学领域:

  • 生物统计学 生物统计学
  • 机器学习 机器学习
  • 临床决策支持 临床决策支持

背景情况:

  • 个性化治疗规则 (ITR) 根据患者的特征来定制医疗决策.
  • 优化ITR通常涉及平衡初级治疗目标与二次结果考虑.
  • 现有的方法可能无法充分解决最大限度地提高初级效益和最大限度地减少二次危害的双重目标.

研究的目的:

  • 开发一个ITR,优化主要结果,同时密切接近二次结果的最佳规则.
  • 引入一项新的"合并罚款",使ITR与不同的结果保持一致.
  • 提出和验证用于估计这些多目标ITR的算法.

主要方法:

  • 开发一种融合惩罚,将ITR与初级结果和二级结果联系起来.
  • 建议使用替代损失函数用于ITR估计的两个算法.
  • 对ITR协议的收率的理论分析.
  • 对价值函数和错误分类率的非对称性属性的推导.

主要成果:

  • 拟议的方法表明,与忽视它们相比,对二次结果的估计和最佳ITR之间的协议率更快地趋同.
  • 建立了对价值函数和错误分类率的理论保证.

更多相关视频

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
Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method
07:12

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method

Published on: August 2, 2021

3.5K

相关实验视频

Last Updated: Jun 11, 2025

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
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
Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method
07:12

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method

Published on: August 2, 2021

3.5K
  • 模拟研究和现实数据示例验证了该方法的有限样本性能.
  • 结论:

    • 合并处罚有效地鼓励ITR考虑主要和次要结果.
    • 拟议的算法提供了一个统计学上合理的方法来学习多目标ITR.
    • 这种方法提供了一个有前途的工具,通过平衡竞争治疗目标来改善临床决策.