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Related Concept Videos

Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

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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...
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Disturbances in Heart Rhythm01:29

Disturbances in Heart Rhythm

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Arrhythmia or dysrhythmia refers to an abnormal heart rhythm caused by a defect in the heart's conduction system. It can cause the heart to beat irregularly, too quickly, or too slowly, leading to symptoms like chest pain, shortness of breath, and fainting. Factors such as stress, caffeine, alcohol, nicotine, cocaine, certain drugs, congenital defects, diseases, and electrolyte abnormalities can trigger arrhythmias.
Arrhythmias are categorized by their speed, rhythm, and origin. A slow heart...
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Mechanism of Cardiac Arrhythmias01:28

Mechanism of Cardiac Arrhythmias

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Arrhythmias are irregular heart rhythms occurring when the heart's electrical impulses become abnormal. These disturbances can lead to various symptoms, depending on their severity and the underlying cause. Some common factors contributing to arrhythmias include hypoxia, ischemia, electrolyte imbalances, excessive catecholamine exposure, drug toxicity, and muscle overstretching. Arrhythmias can be classified into two main types based on the rate and site of origin of abnormal heart rhythms.
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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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ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias01:25

ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias

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Arrhythmia is a condition characterized by an irregular heart rhythm, with ECG changes that differ based on its origin and nature. The types of arrhythmias discussed below include atrial, junctional, and ventricular arrhythmias.Atrial ArrhythmiasPremature Atrial Complexes (PACs): PACs are early atrial beats caused by stress, caffeine, alcohol, electrolyte imbalances, hypoxia, hyperthyroidism, or certain medications (e.g., bronchodilators and decongestants). The ECG shows early P waves with an...
446
ECG Interpretation of Arrhythmias I: Sinus Arrhythmias01:16

ECG Interpretation of Arrhythmias I: Sinus Arrhythmias

738
Arrhythmias are disturbances in the heart's rhythm that lead to abnormal heartbeats. These irregularities can originate from different parts of the heart and are classified based on their origin and nature.
Types of Arrhythmias
Sinus Node Arrhythmias
Sinus Bradycardia: Originating from the sinoatrial (SA) node, sinus bradycardia involves slower impulses, resulting in a heart rate of less than 60 beats per minute (bpm). Causes include sleep, vagal stimulation, beta-blockers, hypothyroidism,...
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Related Experiment Video

Updated: Jan 12, 2026

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

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ECG-XPLAIM: eXPlainable Locally-adaptive Artificial Intelligence Model for arrhythmia detection from large-scale

Panteleimon Pantelidis1, Samuel Ruipérez-Campillo2, Julia E Vogt2

  • 13rd Department of Cardiology, National and Kapodistrian University of Athens, Athens, Greece.

Frontiers in Cardiovascular Medicine
|November 3, 2025
PubMed
Summary
This summary is machine-generated.

ECG-XPLAIM, an AI model, accurately detects arrhythmias using deep learning and provides interpretable results by highlighting key ECG segments. Its open-source release promotes wider clinical adoption and validation.

Keywords:
arrhythmiaartificial intelligencecardiac signalsdeep learningelectrocardiogramexplainabilitymachine learning

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Area of Science:

  • Artificial Intelligence in Medicine
  • Cardiology
  • Machine Learning for Healthcare

Background:

  • Accurate electrocardiogram (ECG) interpretation is vital for patient outcomes.
  • AI-based ECG classification shows promise but lacks transparency.
  • Limited interpretability hinders clinical adoption of AI in ECG analysis.

Purpose of the Study:

  • To introduce ECG-XPLAIM, a novel deep learning model for interpretable ECG classification.
  • To enhance AI model transparency using Grad-CAM visualization for ECG analysis.
  • To evaluate ECG-XPLAIM's performance and generalizability across various arrhythmias.

Main Methods:

  • Developed ECG-XPLAIM with a 1D inception-style convolutional architecture.
  • Integrated Grad-CAM for visualizing ECG segments driving predictions.
  • Trained on MIMIC-IV and validated on PTB-XL for multiple arrhythmia types.

Main Results:

  • ECG-XPLAIM achieved high diagnostic performance (sensitivity, specificity, AUROC > 0.9) on MIMIC-IV.
  • External validation on PTB-XL confirmed generalizability, with AUROC > 0.95 for AFib and STach.
  • Grad-CAM identified physiologically relevant ECG segments and potential misclassification patterns.

Conclusions:

  • ECG-XPLAIM effectively combines high diagnostic accuracy with interpretability in ECG analysis.
  • The open-source release of ECG-XPLAIM facilitates broader adoption and further research.
  • Addressing AI interpretability limitations can accelerate clinical integration of AI-driven ECG tools.