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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

5.3K
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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Acute Coronary Syndrome III: Diagnostic Studies01:30

Acute Coronary Syndrome III: Diagnostic Studies

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Diagnosing acute coronary syndrome or ACS begins with a thorough patient history. Notable symptoms include central, crushing chest pain radiating to the left arm, neck, jaw, or back, along with shortness of breath, sweating (diaphoresis), nausea, vomiting, dizziness, and palpitations.It is crucial to note any history of cardiac illnesses and assess risk factors, including age, gender, smoking, hypertension, diabetes, hyperlipidemia, and a sedentary lifestyle.During physical examination, vital...
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Acute Coronary Syndrome I: Introduction01:30

Acute Coronary Syndrome I: Introduction

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Acute Coronary Syndrome (ACS) encompasses a spectrum of heart conditions caused by sudden obstruction of coronary arteries, typically resulting from the rupture of an atherosclerotic plaque and subsequent thrombus (blood clot) formation. This obstruction can lead to partial or complete blockage of blood flow, causing varying degrees of myocardial ischemia or infarction.ACS includes the following clinical entities:Unstable Angina (UA)Non-ST-Elevation Myocardial Infarction (NSTEMI)ST-Elevation...
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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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Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

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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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Related Experiment Video

Updated: Jan 13, 2026

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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AI-Enabled ECG Analysis Improves Diagnostic Accuracy and Reduces False STEMI Activations: A Multicenter U.S.

Robert Herman1, Bryn E Mumma2, Jake D Hoyne3

  • 1Cardiovascular Center Aalst, AZORG Hospital, Aalst, Belgium; Powerful Medical, Bratislava, Slovakia.

JACC. Cardiovascular Interventions
|October 29, 2025
PubMed
Summary

Artificial intelligence (AI) ECG analysis significantly improved ST-segment elevation myocardial infarction (STEMI) detection and reduced false activations. This AI tool enhances recognition of atypical STEMI presentations, supporting its integration into acute chest pain protocols.

Keywords:
ST-segment elevation myocardial infarctionacute coronary syndromeartificial intelligenceelectrocardiographypercutaneous coronary intervention

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Area of Science:

  • Cardiology
  • Medical Artificial Intelligence
  • Health Informatics

Background:

  • Timely reperfusion is crucial for reducing mortality in ST-segment elevation myocardial infarction (STEMI).
  • Current ECG-guided cardiac catheterization laboratory (CCL) activation improves response but faces diagnostic uncertainty, leading to false-positive activations (FPAs) and delays, especially with atypical presentations.

Purpose of the Study:

  • To evaluate the diagnostic performance of AI-based ECG analysis in real-world STEMI triage.
  • To assess the operational impact of AI in multicenter STEMI diagnosis across a U.S. registry.

Main Methods:

  • Retrospective analysis of 1,032 patients with suspected STEMI undergoing emergent CCL activation across three U.S. PCI centers (Jan 2020-May 2024).
  • Comparison of standard triage with blinded retrospective AI ECG analysis (Queen of Hearts, PMcardio) for detecting acute coronary occlusion and mimics.
  • Reference standard: angiographically confirmed culprit lesion with positive enzymes. Analysis included diagnostic accuracy, subgroup performance, and FPA reclassification.

Main Results:

  • AI ECG analysis demonstrated superior sensitivity (92.0%) versus standard triage (71.0%) for STEMI detection (p < 0.001).
  • AI significantly reduced false-positive activation rates (7.9% vs. 41.8%) and improved specificity (81.0% vs. 29.0%) (p < 0.001).
  • AI achieved an AUC of 0.94, maintaining performance across challenging subgroups and correctly reclassifying 91% of biomarker-negative FPAs.

Conclusions:

  • AI-based ECG analysis substantially enhances STEMI detection accuracy and reduces unnecessary interventions.
  • The AI model effectively identifies non-conventional STEMI presentations, addressing diagnostic uncertainty.
  • Findings support the integration of AI-ECG analysis into acute chest pain management pathways for improved patient outcomes.