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Related Concept Videos

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...
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Cardiomyopathy III: Hypertrophic Cardiomyopathy01:29

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Hypertrophic cardiomyopathy, or HCM, is an autosomal dominant genetic disorder characterized by asymmetric left ventricular hypertrophy without ventricular dilation. It is more common in men and is typically diagnosed in young, athletic adults.EtiologyHCM is primarily genetic and is caused by mutations in genes encoding sarcomeric proteins. Researchers have identified over 1400 mutations across at least 11 different genes. Among these, the most frequently occurring mutations are found in the...
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Electrocardiogram Fundamentals01:28

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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
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Imaging Studies for Cardiovascular System I:Echocardiography01:17

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Cardiac imaging studies encompass a wide range of noninvasive and minimally invasive techniques designed to visualize the heart's structure and function in detail. One such technique is echocardiography, which uses high-frequency ultrasound waves to produce detailed images of the heart, known as echocardiograms.
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Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

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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...
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Related Experiment Video

Updated: Mar 6, 2026

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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Deep learning-enabled ECG system for detecting left ventricular hypertrophy and predicting cardiovascular prognoses.

Zhe-Yu Yang1,2, Shi-Chue Hsing3, Dung-Jang Tsai4

  • 1Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China.

Biodata Mining
|March 4, 2026
PubMed
Summary

A new deep learning model (DLM) using electrocardiograms (ECG) effectively detects left ventricular hypertrophy (LVH) and predicts cardiovascular risks, offering a simpler screening method.

Keywords:
Artificial intelligenceCardiovascular diseaseDeep learningElectrocardiogramLeft ventricular hypertrophyPrevivor

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Evaluation of Left Ventricular Structure and Function using 3D Echocardiography
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Evaluation of Left Ventricular Structure and Function using 3D Echocardiography

Published on: October 28, 2020

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Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Medical Diagnostics

Background:

  • Left ventricular hypertrophy (LVH) affects 15-20% of the population.
  • Current ECG criteria for LVH lack sensitivity and optimal prognostic value.
  • Deep learning models (DLMs) show promise for improving cardiovascular risk assessment.

Purpose of the Study:

  • To develop a DLM-enabled ECG system for LVH detection.
  • To assess the prognostic associations of the AI-ECG-LVH model with cardiovascular outcomes.
  • To provide a noninvasive tool for LVH screening and risk stratification.

Main Methods:

  • Developed and validated a DLM-enabled ECG system (AI-ECG-LVH) using data from 40,736 patients (Hospital A) and 6,271 patients (Hospital B).
  • Defined LVH using left ventricular mass index (LVMI) from echocardiography.
  • Evaluated prognostic outcomes including acute myocardial infarction (AMI), heart failure (HF), and atrial fibrillation (AFib).

Main Results:

  • The AI-ECG-LVH model achieved AUCs of 0.82 (males) and 0.77 (females) in external validation.
  • Hazard ratios for incident AMI, HF, and AFib were comparable to echocardiography-defined LVH (ECHO-LVH).
  • AI-ECG-LVH showed hazard ratios of 2.67 (AMI), 3.15 (HF), and 2.23 (AFib).

Conclusions:

  • The AI-ECG-LVH model offers a straightforward, affordable, and noninvasive approach for LVH screening.
  • This AI-ECG-LVH system aids in first-contact cardiovascular risk stratification.
  • DLM-enabled ECG analysis represents a significant advancement in cardiovascular diagnostics.