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相关概念视频

Disturbances in Heart Rhythm01:28

Disturbances in Heart Rhythm

970
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...
970
Mechanism of Cardiac Arrhythmias01:28

Mechanism of Cardiac Arrhythmias

925
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.
925
ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias01:25

ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias

21
Arrhythmia is a condition characterized by an irregular heart rhythm, with ECG changes that differ based on its origin and nature. The types of arrhythmias discussed below include atrial, junctional, and ventricular arrhythmias.Atrial ArrhythmiasPremature Atrial Complexes (PACs): PACs are early atrial beats caused by stress, caffeine, alcohol, electrolyte imbalances, hypoxia, hyperthyroidism, or certain medications (e.g., bronchodilators and decongestants). The ECG shows early P waves with an...
21
Pulse rhythm01:30

Pulse rhythm

807
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...
807
ECG Interpretation of Arrhythmias I: Sinus Arrhythmias01:16

ECG Interpretation of Arrhythmias I: Sinus Arrhythmias

217
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,...
217
Antiarrhythmic Drugs: Class II Agents as β-Adrenergic Blockers01:24

Antiarrhythmic Drugs: Class II Agents as β-Adrenergic Blockers

747
Adrenergic stimulation generally impacts cardiac rate and rhythm. Specifically, stimulation of the β-adrenoceptors triggers an increase in intracellular calcium ion influx and pacemaker currents, which may cause arrhythmias. Catecholamines like adrenaline also demonstrate β2-adrenoceptor-mediated hypokalemia, impacting cardiac action potential and disrupting the normal cardiac rhythm. Class II antiarrhythmic drugs are β-adrenoceptor antagonists or β-blockers, which...
747

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Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
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领域和患者对抗性多任务学习为心律失常的分类.

Dawnlicity Charls, Mostafa Shahin, Beena Ahmed

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 12, 2023
    PubMed
    概括
    此摘要是机器生成的。

    使用机器学习的自动心律失常检测通过对抗式多任务学习 (AMTL) 得到了改进. 这种方法增强了不同数据集的心电图 (ECG) 分析,提高了诊断准确性和F1分数,以获得更好的患者结果.

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    科学领域:

    • 人工智能的人工智能
    • 心脏病学 心脏病学
    • 机器学习 机器学习

    背景情况:

    • 手动对心电图 (ECG) 进行心律失常的查是耗时的.
    • 自动诊断模型受到小型临床数据集的限制.
    • 需要使用多个数据集的训练模型来改进心律失常的分类.

    研究的目的:

    • 提出对抗式多任务学习 (AMTL) 来从心电图数据库中提取域和患者不变特征.
    • 调查节拍细分和规范化对域不变性的影响.
    • 为了提高心律失常分类的准确性和F1分数,使用AMTL.

    主要方法:

    • 利用对抗式多任务学习 (AMTL) 在两个不同的心电图数据库 (MIT-BIH 节律失常和圣彼得堡 INCART) 上训练模型.
    • 研究了节拍细分位置和节拍规范化技术对实现域不变性的影响.
    • 对比域名对抗模型与非对抗模型的性能.

    主要成果:

    • 与没有域对抗学习的模型相比,域对抗模型显示出更高的准确性和平均F1分数.
    • 拟议的患者和领域对抗模型在两个测试数据库中显著提高了F1分数,从70%和74%提高到77%.
    • 节拍细分位置和正常化影响了所达到的域不变度的程度.

    结论:

    • 具有多个数据集和多个对抗任务的对抗式多任务学习有效地提高了F1对心律失常分类的得分.
    • 在训练心律失常的自动诊断模型方面,AMTL提供了一种有希望的方法来克服数据的局限性.
    • 这些发现确定了AMTL在改善心电图分析和患者护理方面的临床相关性.