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相关概念视频

Electrocardiogram01:29

Electrocardiogram

2.5K
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...
2.5K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

653
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...
653
Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

42
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.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...
42
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

7.4K
The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
7.4K

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相关实验视频

Updated: Jul 28, 2025

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

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一个可解释的人工智能启用心电图分析模型用于左心室功能减弱的分类.

Susumu Katsushika1, Satoshi Kodera1, Shinnosuke Sawano1

  • 1Department of Cardiovascular Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.

European heart journal. Digital health
|June 2, 2023
PubMed
概括
此摘要是机器生成的。

我们开发了一种可解释的人工智能 (AI) 模型,使用心电图 (ECG) 来识别左心室排气小部分 (LVEF) 的减少. 人工智能模型的AI模型

关键词:
人工智能的人工智能是人工智能.心声回声扫描 (Echocardiography) 是一种心声回声扫描.电心电图 (ECG) 是一种心电图.可解释的人工智能左心室功能障碍是什么机器学习是机器学习.

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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

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相关实验视频

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Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

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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
  • 医疗信息学 医疗信息学

背景情况:

  • 这是一个很棒的节目,这是一个很棒的节目.
  • 黑盒子是一个黑盒子.
  • 人工智能 (AI) 的性质限制了其临床应用.
  • 开发可解释的AI模型对于临床实践至关重要.
  • 减少左心室喷射率 (LVEF) 是心脏健康的重要指标.

研究的目的:

  • 开发一种人工智能模型,使用12导电心电图来对LVEF降低的患者进行分类.
  • 确保人工智能模型为临床使用提供决策解释性.

主要方法:

  • 在29907个ECG上训练了一种随机森林模型,以识别减少的LVEF.
  • 沙普利添加剂解释 (SHAP) 被应用到提取决策标准.
  • 提取的标准被聚类并视觉解释为临床相关性.

主要成果:

  • 人工智能模型使用六个关键心电图结果确定了减少的LVEF.
  • 这些标准在中央和合作数据集中一致.
  • 在解释了标准后,心脏病学家的准确性从62.9%提高到73.9%.

结论:

  • 开发了一个可解释的AI模型,用于使用ECG减少LVEF分类.
  • 该模型的决策标准基于特定的ECG发现,具有临床相关性.
  • 这种可解释的AI方法可以增强心脏病学中的临床决策.