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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

3.9K
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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Pulse rhythm01:30

Pulse rhythm

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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...
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Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

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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
An ECG utilizes electrodes on the skin...
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Related Experiment Video

Updated: Oct 18, 2025

Simultaneous Video-EEG-ECG Monitoring to Identify Neurocardiac Dysfunction in Mouse Models of Epilepsy
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Deep-learning model for screening sepsis using electrocardiography.

Joon-Myoung Kwon1,2,3,4, Ye Rang Lee5, Min-Seung Jung6

  • 1Artificial Intelligence and Big Data Research Center, Sejong Medical Research Institute, Bucheon, Republic of Korea. kwonjm@sejongh.co.kr.

Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine
|October 4, 2021
PubMed
Summary
This summary is machine-generated.

A deep learning model (DLM) effectively screens for sepsis using electrocardiography (ECG), demonstrating high accuracy across various lead types. This innovation aids in early detection and prevention of severe outcomes, improving patient care.

Keywords:
Artificial intelligenceDeep learningElectrocardiographyInfectionsSepsisShock, Septic

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Area of Science:

  • Biomedical Engineering
  • Artificial Intelligence in Medicine
  • Cardiology

Background:

  • Sepsis is a critical global health issue characterized by life-threatening organ dysfunction.
  • Early sepsis detection is challenging, necessitating advanced screening tools.
  • Electrocardiography (ECG) offers a potential non-invasive method for sepsis screening.

Purpose of the Study:

  • To develop and validate a deep learning model (DLM) for sepsis screening using ECG.
  • To assess the DLM's performance across different ECG lead configurations (12-lead, 6-lead, single-lead).
  • To evaluate the DLM's applicability in diverse clinical settings through external validation.

Main Methods:

  • Retrospective cohort study involving over 46,000 patients from two hospitals.
  • Development of a DLM using a large dataset of 73,727 ECGs from 18,142 patients.
  • Internal and external validation of the DLM using independent ECG datasets.

Main Results:

  • The DLM achieved high diagnostic accuracy, with AUCs of 0.901 for sepsis and 0.906 for septic shock using 12-lead ECG during internal validation.
  • External validation demonstrated robust performance, with AUCs of 0.863 for sepsis and 0.899 for septic shock.
  • The model showed good performance with 6-lead and single-lead ECGs (AUC 0.845-0.882) and predicted in-hospital mortality in infectious disease patients (AUC 0.817).

Conclusions:

  • The DLM demonstrates reliable performance for sepsis screening using various ECG lead types.
  • The findings suggest that DLM-powered sepsis screening is feasible with both conventional and portable ECG devices.
  • This approach holds promise for preventing disease progression and reducing mortality associated with sepsis.