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

Electrocardiogram01:29

Electrocardiogram

5.6K
An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
5.6K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

1.4K
Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
1.4K
Physiological Foundation of Stress01:24

Physiological Foundation of Stress

603
Stress triggers a coordinated physiological response involving the sympathetic nervous system (SNS) and the hypothalamic-pituitary-adrenal (HPA) axis. This dual activation ensures that the body is prepared for both immediate and prolonged stress management. The process begins with the perception of a stressor. This initial phase activates the SNS, leading to the rapid release of adrenaline (epinephrine) from the adrenal glands.
Role of the Sympathetic Nervous System
Adrenaline triggers the...
603
Social Foundations of Self II: The Generalized Other01:20

Social Foundations of Self II: The Generalized Other

241
According to George Herbert Mead, as children progress beyond the game stage, they develop a more comprehensive understanding of societal rules and norms. This cognitive and social development enables them to internalize the expectations of the broader community, refining their ability to regulate behavior.Consistent participation in organized activities is crucial in helping children recognize that their actions are not isolated but contribute to a more significant, interconnected group...
241
Theoretical Foundations of Nursing Practice01:30

Theoretical Foundations of Nursing Practice

17.3K
Theories play an essential role in organizing patient care. Theories refer to a proposed or followed belief, policy, or procedure that is the basis for action. Nursing theories are knowledge-based concepts that guide nurses' actions, influence nursing education and practice, and allow nurses to care for their patients.
Theories provide a perspective to assess patients' conditions and organize data and methods. They also assist in analyzing and interpreting information. They represent a...
17.3K
Social Foundations of Self I: Play and Game01:24

Social Foundations of Self I: Play and Game

195
The development of self in children is deeply rooted in social interactions, mainly through stages of play and structured games. These stages, outlined by sociologist George Herbert Mead, illustrate how children progressively learn to understand and adopt social roles, forming a cohesive sense of self.The Play Stage: Imitation and Simple Role-TakingIn the early years of childhood, the play stage is characterized by imitative behavior, where children engage in role-playing based on familiar...
195

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

Advancing Cardiogeriatric Care and Frailty Science in Cardiovascular Disease: From Basic Science to Implementation.

Heart, lung & circulation·2026
Same author

Association of deep learning-derived temporalis sarcopenia with mortality in acute ischemic stroke.

The journals of gerontology. Series A, Biological sciences and medical sciences·2026
Same author

Tetralogy of Fallot: electrophysiology-guided surgical ablation during pulmonary valve replacement.

European heart journal·2026
Same author

DeepECG.ai: An AI-enhanced ECG analysis platform to bridge the expertise gap from primary care to cardiology.

Journal of electrocardiology·2026
Same author

Automated echocardiographic detection of mitral valve prolapse and mitral regurgitation with video-based artificial intelligence algorithms.

European heart journal. Digital health·2026
Same author

Scope and Outcome of Early Repolarization Syndrome in Unexplained Cardiac Arrest: Insights From the National HiRO Registry.

Circulation. Arrhythmia and electrophysiology·2026
Same journal

The surgical collateralization theory: has the beautiful hypothesis been killed by the ugly facts?

European heart journal·2026
Same journal

Beyond single measurement: additional considerations for high-sensitivity C-reactive protein in cardiovascular risk prediction.

European heart journal·2026
Same journal

Brain mineralocorticoid receptor activation and antagonism in heart failure with preserved ejection fraction: a hypothesis.

European heart journal·2026
Same journal

Myths and misconceptions about high-sensitivity C-reactive protein as a marker of residual inflammatory risk.

European heart journal·2026
Same journal

Vascular Ehlers-Danlos syndrome: should we treat asymptomatic patients?

European heart journal·2026
Same journal

Impactful trials on dyslipidaemias, fractional flow reserve, beta-blockers, and peripheral artery disease.

European heart journal·2026
查看所有相关文章

相关实验视频

Updated: Jan 23, 2026

Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies
10:09

Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies

Published on: September 22, 2014

13.6K

基础模型用于心电图解读:临床影响.

Alexis Nolin-Lapalme1,2,3,4, Achille Sowa1,2,4, Jacques Delfrate2,4

  • 1Department of Biochemistry and Molecular Medicine, Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada H3C 3J7.

European heart journal
|January 22, 2026
PubMed
概括
此摘要是机器生成的。

本研究介绍了用于心电图 (ECG) 解释的两个开源人工智能 (AI) 模型. 自主监督学习 (SSL) 显示出改善心脏护理中的AI诊断的前景,特别是在有限的数据的情况下.

关键词:
人工智能的人工智能是人工智能.这就是CLSA CLSA.电心电图 (ECG) 是一种心电图.公平的 公平的 公平的基金会模型 基金会模型可以概括的概括性隐私 隐私 隐私 隐私 隐私 隐私英国生物银行

更多相关视频

Electrocardiogram Recordings in Anesthetized Mice using Lead II
04:16

Electrocardiogram Recordings in Anesthetized Mice using Lead II

Published on: June 20, 2020

14.1K
A Model to Simulate Clinically Relevant Hypoxia in Humans
09:54

A Model to Simulate Clinically Relevant Hypoxia in Humans

Published on: December 22, 2016

9.3K

相关实验视频

Last Updated: Jan 23, 2026

Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies
10:09

Transferring Cognitive Tasks Between Brain Imaging Modalities: Implications for Task Design and Results Interpretation in fMRI Studies

Published on: September 22, 2014

13.6K
Electrocardiogram Recordings in Anesthetized Mice using Lead II
04:16

Electrocardiogram Recordings in Anesthetized Mice using Lead II

Published on: June 20, 2020

14.1K
A Model to Simulate Clinically Relevant Hypoxia in Humans
09:54

A Model to Simulate Clinically Relevant Hypoxia in Humans

Published on: December 22, 2016

9.3K

科学领域:

  • 人工智能在医学中的应用
  • 心血管诊断心血管诊断服务
  • 机器学习用于医疗保健

背景情况:

  • 目前用于ECG解释的AI往往缺乏概括性,并且依赖于带有广泛标记数据的监督学习 (SL).
  • 自主监督学习 (SSL) 通过从未标记的数据中学习提供了一个潜在的解决方案,克服了传统方法的局限性.
  • 这项研究解决了在心脏诊断中适应性,开源AI解决方案的需求.

研究的目的:

  • 开发和比较两个开源基础ECG模型:DeepECG-SL (监督) 和DeepECG-SSL (自我监督).
  • 评估SSL与SL在不同临床环境中的ECG解释中的通用性,公平性和性能.
  • 提供可访问的人工智能工具,以进行强大且数据效率高的心脏诊断.

主要方法:

  • 在超过100万个心电图上训练了两个模型,DeepECG-SL和DeepECG-SSL,以预测77种心脏疾病.
  • 在微调之前,DeepECG-SSL使用了对比学习和掩盖的模拟在未标记的数据上.
  • 评估了7个私营和4个公共多语言医疗保健系统的绩效,包括公平性和隐私性评估.

主要成果:

  • 这两种模型在内部,公共和私人外部数据集中都实现了高性能 (AUROCs ~0.98-0.99).
  • DeepECG-SSL在有限的数据任务中表现出卓越的表现,例如长QT综合征基因型分类和心房动风险预测.
  • 公平性分析表明,这两种模型的年龄和性别差异极小.

结论:

  • 自主监督学习 (SSL) 是对心电图分析的一个有希望的范式,提高了人工智能驱动的心脏诊断的可访问性,可泛化性和公平性.
  • 模型,工具和代码的开源发布旨在促进强大的,数据高效的AI诊断.
  • 在临床环境中,SSL模型特别有用,因为注释数据有限.