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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

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 the T...
Acute Coronary Syndrome III: Diagnostic Studies01:30

Acute Coronary Syndrome III: Diagnostic Studies

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...
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

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: Jun 19, 2026

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
18:11

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Published on: December 28, 2012

Sex-Consistent Performance of an AI-Enabled ECG for Acute Myocardial Infarction: The ROMIAE Study.

Hak Seung Lee1, Sora Kang1, Joon-Myoung Kwon2

  • 1Medical AI Co., Ltd., Seoul, Republic of Korea; Digital Healthcare Institute, Sejong Hospital, Republic of Korea.

JACC. Advances
|June 18, 2026
PubMed
Summary

Artificial intelligence-enabled electrocardiogram (AI-ECG) shows reliable accuracy for detecting acute myocardial infarction (AMI) in both women and men. This AI tool demonstrates safe and consistent performance for ruling out AMI across diverse patient groups.

Keywords:
AI-ECGacute myocardial infarctionartificial intelligenceelectrocardiogram

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Area of Science:

  • Cardiology
  • Medical Artificial Intelligence
  • Diagnostic Tools

Background:

  • Women face higher risks of delayed or missed acute myocardial infarction (AMI) diagnosis.
  • Artificial intelligence-enabled electrocardiogram (AI-ECG) offers potential for earlier AMI detection.
  • Limited prospective data exists on AI-ECG's sex-consistent performance and safety in ruling out AMI.

Purpose of the Study:

  • To assess the sex-stratified diagnostic performance of an AI-ECG system for AMI.
  • To evaluate the rule-out safety and phenotype robustness of AI-ECG in a prospective emergency department cohort.
  • To validate AI-ECG's effectiveness across different sexes in a real-world clinical setting.

Main Methods:

  • The ROMIAE study prospectively validated AI-ECG across 18 South Korean centers.
  • AI-ECG analyzed initial electrocardiograms (ECGs) for suspected AMI in 8,493 adults, including 3,186 women.
  • Diagnostic performance and rule-out safety were assessed using receiver-operating characteristic curves, sensitivity, negative predictive value, and missed AMI rates, with sex-stratified analyses.

Main Results:

  • AI-ECG exhibited comparable diagnostic discrimination between women (AUC 0.875) and men (AUC 0.871).
  • At the low-risk cutoff, rule-out sensitivity was high in women (98.8%) and men (99.8%), with excellent negative predictive values.
  • Missed AMI rates were low (<1%) in both sexes, with stable performance across different myocardial infarction types and no degradation in women.

Conclusions:

  • AI-ECG demonstrates sex-consistent diagnostic performance for AMI in a large, prospective emergency department cohort.
  • The AI-ECG system maintains high rule-out safety for AMI, performing reliably in both women and men.
  • Further validation and implementation studies are recommended to integrate AI-ECG into clinical practice for improved AMI diagnosis.