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相关概念视频

Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

22
Dysrhythmias, also known as arrhythmias, are disturbances in the heart's rhythm that range from benign to life-threatening. A thorough evaluation is crucial for appropriate management and involves a comprehensive medical history, physical examination, and various diagnostic tests.1. Medical HistorySymptoms: Collect detailed information on palpitations, dizziness, syncope, chest pain, and fatigue. Note their onset, frequency, and triggers.Previous Cardiac Issues: Document any history of heart...
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Electrocardiogram01:29

Electrocardiogram

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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...
2.2K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

542
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...
542
Pulse rhythm01:30

Pulse rhythm

769
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...
769
Dysrhythmias I: Introduction01:15

Dysrhythmias I: Introduction

4
Dysrhythmias refers to abnormalities in the heart's rhythm. They result from disruptions in the heart's electrical conduction system, which includes the sinoatrial(SA)node, atrioventricular(AV) node, the bundle of His, bundle branches, and Purkinje fibers.Definition and PathophysiologyDysrhythmias result from disorders of impulse formation, impulse conduction, or both. The heart contains specialized cells in the sinoatrial node, atrioventricular node, and the bundle of His and Purkinje fibers...
4
Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

3
Holter monitoring is a continuous electrocardiography (ECG) recording that tracks the heart's electrical activity over an extended period, generally 24 to 48 hours. This noninvasive diagnostic tool detects irregular heart rhythms that may not be captured during a standard ECG performed in a clinical setting.DeviceThe Holter monitor is a portable, small device connected to several electrodes on the patient's chest. These electrodes detect the heart's electrical signals and transmit them to the...
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相关实验视频

Updated: Jun 11, 2025

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
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基于心电图的深度学习算法的开发,用于检测基于心电图的失血症.

Jung Nam An1, Minje Park2, Sunghoon Joo2

  • 1Division of Nephrology, Department of Internal Medicine, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, 22, Gwanpyeong-ro 170 Beon-gil, Dongan-gu, Anyang-si, Gyeonggi-do, 14068, Republic of Korea.

Scientific reports
|October 1, 2024
PubMed
概括
此摘要是机器生成的。

深度学习模型可以使用心电图 (ECG) 检测高卡莱米亚和低卡莱米亚. 这种非侵入性方法有助于早期诊断失调血症,可能改善患者的治疗结果,并降低致命心律失常的风险.

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科学领域:

  • 心脏病学 心脏病学
  • 人工智能在医学中的应用
  • 医学诊断 医学诊断 医学诊断

背景情况:

  • 失血症是一种电解质失衡,带来风险,包括致命的心律失常.
  • 及时监测血清水平对于管理失血症至关重要.
  • 电心电图 (ECG) 提供了一种非侵入性和快速的患者评估方法.

研究的目的:

  • 开发和验证深度学习模型,从心电图数据中检测高卡莱米亚和低卡莱米亚.
  • 评估这些人工智能驱动模型的诊断性能和临床实用性.
  • 探索心电图片段的可解释性,以预测失血症.

主要方法:

  • 一个回顾性队列研究,涉及超过45万个ECG-样本从2006-2020.
  • 开发深度学习算法,训练使用12,四肢和I心电图.
  • 使用内部和外部测试队伍验证模型,评估诊断指标,如AUROC,灵敏度和特异性.

主要成果:

  • 深度学习模型在高卡利米亚 (AUROC高达0.929) 和低卡利米亚 (AUROC高达0.925) 方面实现了高的诊断性能.
  • 模型在不同的ECG导电配置中显示出强烈的灵敏度和特异性.
  • 根据模型确定患有高血症的患者表现出明显较低的30天生存率 (p < 0.001).

结论:

  • 深度学习模型可以从心电图上准确地检测出高血和低血.
  • 这些模型显示出在临床实践中进行简单,快速和非侵入性硬血症诊断的潜力.
  • 这些人工智能工具所促进的早期检测和干预可以改善患者的治疗结果.