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相关概念视频

Disturbances in Heart Rhythm01:28

Disturbances in Heart Rhythm

936
Arrhythmia or dysrhythmia refers to an abnormal heart rhythm caused by a defect in the heart's conduction system. It can cause the heart to beat irregularly, too quickly, or too slowly, leading to symptoms like chest pain, shortness of breath, and fainting. Factors such as stress, caffeine, alcohol, nicotine, cocaine, certain drugs, congenital defects, diseases, and electrolyte abnormalities can trigger arrhythmias.
Arrhythmias are categorized by their speed, rhythm, and origin. A slow...
936
Pulse rhythm01:30

Pulse rhythm

785
Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
785
Electrocardiogram01:29

Electrocardiogram

2.3K
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...
2.3K
Mechanism of Cardiac Arrhythmias01:28

Mechanism of Cardiac Arrhythmias

912
Arrhythmias are irregular heart rhythms occurring when the heart's electrical impulses become abnormal. These disturbances can lead to various symptoms, depending on their severity and the underlying cause. Some common factors contributing to arrhythmias include hypoxia, ischemia, electrolyte imbalances, excessive catecholamine exposure, drug toxicity, and muscle overstretching. Arrhythmias can be classified into two main types based on the rate and site of origin of abnormal heart rhythms.
912
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

566
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...
566
ECG Interpretation of Arrhythmias I: Sinus Arrhythmias01:16

ECG Interpretation of Arrhythmias I: Sinus Arrhythmias

211
Arrhythmias are disturbances in the heart's rhythm that lead to abnormal heartbeats. These irregularities can originate from different parts of the heart and are classified based on their origin and nature.
Types of Arrhythmias
Sinus Node Arrhythmias
Sinus Bradycardia: Originating from the sinoatrial (SA) node, sinus bradycardia involves slower impulses, resulting in a heart rate of less than 60 beats per minute (bpm). Causes include sleep, vagal stimulation, beta-blockers, hypothyroidism,...
211

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相关实验视频

Updated: Jun 25, 2025

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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人工智能用于使用门诊心电图的腹腔失常能力.

Joseph Barker1,2,3,4,5, Xin Li1,6, Ahmed Kotb1,2

  • 1Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Groby Road, Leicester LE3 9QP, UK.

European heart journal. Digital health
|May 22, 2024
PubMed
概括

一个人工智能模型,VA-ResNet-50,可以从心电图 (ECG) 高度准确地预测腹腔失常 (VA) 风险. 这种人工智能工具有望改善患者的治疗结果,并指导植入式心脏转移器除器的使用.

关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.可植入的心脏转换器除器神经网络的神经网络的神经网络风险分层是指风险的分层.室腔心律不整 室腔心律不整

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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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相关实验视频

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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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科学领域:

  • 心脏病学 心脏病学
  • 人工智能的人工智能
  • 医学诊断 医学诊断 医学诊断

背景情况:

  • 目前对植入式心脏转移器除器 (ICD) 的临床指南在准确分层室内节律失常 (VA) 风险方面存在局限性.
  • 这种不准确性导致了显著的患者发病率和死亡率.
  • 人工智能 (AI) 提出了一种新的VA风险分层方法,使用心电图 (ECG).

研究的目的:

  • 开发和验证用于VA风险分层的深度神经网络 (DNN).
  • 评估AI的能力,以确定常规的门诊心电图的VA风险.

主要方法:

  • 一项多中心病例控制研究使用了基于ResNet-50的开源DNN,VA-ResNet-50.
  • 该模型分析了三导,24小时的门诊心电图,以预测VA能力.
  • 包括270名成年患者 (159名VA患者),在VA事件发生前长达1.6年的时间内收集了心电图.

主要成果:

  • 在从ECG分类VA能力时,VA-ResNet-50获得了0.76的准确度和0.79的F1得分.
  • 该模型显示,接收机操作员曲线下的面积为0.8.8.
  • 人工智能确定为高风险的个人,VA的相对风险是VA的2.87倍.

结论:

  • 在VA-ResNet-50分析时,门诊心电图包含了对VA分层的有价值的风险信号.
  • 人工智能模型的性能超过了当前的医疗指南.
  • 这种由人工智能驱动的方法对优化分配拯救生命的ICD充满希望.