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Cardiology collaboration advances machine learning predictions for AFib after stroke

Medical Xpress - Cardiology

Researchers at Penn State are using machine learning and existing electrocardiogram (ECG) data to help doctors make more accurate predictions.

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New AI-powered Algorithm Could Better Assess People’s Risk of Common Heart Condition

DAIC

milla1cf Wed, 12/13/2023 - 10:24 December 13, 2023 — A new artificial intelligence (AI) model designed by Scripps Research scientists could help clinicians better screen patients for atrial fibrillation (or AFib)—an irregular, fast heartbeat that is associated with stroke and heart failure.

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Cardiomatics guide: Analyzing arrhythmias made easy

Cardiomatics

In a world where technology reigns supreme, one of the most profound tools in medicine remains the irreplaceable electrocardiogram (ECG). As technology advances, so too does our ability to capture the heart’s rhythm with greater precision. AFIB/AFL – atrial fibrillation or atrial flutter episodes.

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News from EHRA 2024: International Experts Agree on Standards for Catheter Ablation of Atrial Fibrillation

DAIC

AFib Facts and Impacts Atrial fibrillation is the most common cardiac arrhythmia, affecting 2% of individuals worldwide. Before the procedure, patients should have an electrocardiogram (ECG) and echocardiogram (ultrasound of the heart) to check the heart’s rhythm and function. The risk of death is extremely low (0.05-0.1%).

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Supercharging the ECG: AI set to Revolutionize the Diagnostic Cardiology Market

DAIC

Signify Research has just released a deep-dive qualitative analysis of developments around the use of AI to analyze and interpret electrocardiograms (ECGs), one of the world’s most ubiquitous diagnostic tests for cardiac disease. By 1909 ECGs were being used to diagnose cases of arrhythmia; by 1910 to diagnose indicators of a heart attack.

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