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

Modeling in Therapy01:26

Modeling in Therapy

44
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
44
Treatment Strategies for Psychological Disorders01:24

Treatment Strategies for Psychological Disorders

85
Treatment approaches for psychological disorders fall into three main categories: psychological, biological, and sociocultural. Each approach targets different aspects of mental health, requiring varying levels of education and training.
Psychological therapies focus on modifying emotions, thoughts, and behaviors through talking, interpreting, listening, rewarding, challenging, and modeling. Clinical psychologists, counselors, and social workers commonly practice psychotherapy. Clinical...
85
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

4.8K
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...
4.8K
Data Validation01:03

Data Validation

4.9K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
4.9K
Reliability and Validity01:29

Reliability and Validity

12.7K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
12.7K
Blinding01:11

Blinding

2.4K
Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.
2.4K

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 longer, the better? Investigating the effect of prolonged acoustic stimulation on brief acoustic tinnitus suppression.

BMC neurology·2026
Same author

Trajectory of COVID-related tinnitus over the pandemic timeline.

Brazilian journal of otorhinolaryngology·2026
Same author

Antagonizing NRG1-ERBB4 signaling pathway with spironolactone for the treatment of schizophrenia: results of a randomized controlled drug repositioning clinical trial.

Communications medicine·2026
Same author

Tinnitus and tinnitus disorder: Genetic, neurobiological, and clinical differentiation.

iScience·2026
Same author

Sound hypersensitivity phenotypes and sound hypersensitivity disorder.

Neuroscience and biobehavioral reviews·2026
Same author

E-field guided repetitive transcranial magnetic stimulation modulates oscillatory brain activity dynamics in tinnitus.

Brain research bulletin·2026

相关实验视频

Updated: Jun 3, 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

培训和验证治疗推者与部分验证证据的治疗推者

Vishnu Unnikrishnan1, Clara Puga1, Miro Schleicher1

  • 1Knowledge Management & Discovery Lab, Otto-von-Guericke-University Magdeburg, Germany.

Artificial intelligence in medicine
|January 8, 2025
PubMed
概括

这项研究引入了一种新方法,用于训练使用随机临床试验 (RCT) 数据的临床决策支持系统 (DSS). 该方法可以在临床部署之前进行DSS验证,从而改善治疗建议.

关键词:
临床决策支持 临床决策支持缺乏验证证据的证据治疗建议验证治疗建议的验证.治疗建议者推治疗.

更多相关视频

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers
08:05

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

9.7K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.5K

相关实验视频

Last Updated: Jun 3, 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
A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers
08:05

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

9.7K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

7.5K

科学领域:

  • 医疗信息学 医疗信息学
  • 临床决策支持 临床决策支持
  • 生物统计学 生物统计学

背景情况:

  • 临床决策支持系统 (DSS) 通常是根据特定诊所的观察数据进行训练的.
  • 这限制了它们的应用到已经在随机临床试验 (RCT) 中验证但尚未在临床实践中的治疗方法.
  • 在临床实施之前,需要使用现有的RCT数据来训练和验证DSS的方法.

研究的目的:

  • 开发和验证一种训练和验证DSS核心的方法,使用随机临床试验 (RCT) 的数据.
  • 为了应对RCT数据中缺少的治疗理由和验证证据所带来的挑战.
  • 为了使RCT数据用于临床前DSS培训和验证.

主要方法:

  • 重新建模目标变量以控制一般治疗效应,而不是随机的个人分配.
  • 采用机器学习核心,对缺失的功能强大,并对小数量的患者采用集体方法.
  • 引入反事实性治疗验证,将DSS建议与RCT分配进行比较.

主要成果:

  • 开发的方法成功地利用RCT数据用于DSS学习和验证.
  • 该DSS证明了能够建议改善患者结果的治疗方法的能力.
  • 结果受到RCT数据中每组治疗患者数量有限的限制.

结论:

  • 建立了一个基础,为在RCT中验证但尚未临床部署的治疗方法创建决策支持工具.
  • 实践者可以利用这种方法来训练和验证使用可用的RCT数据的DSS.
  • 未来的工作应该专注于提高预测器的稳定性,可能探索合成数据生成.