Phenotypic Selectivity of Artificial Intelligence-enhanced Electrocardiography in Cardiovascular Diagnosis and Risk Prediction

Abstract excerpt

<h4>Introduction</h4> Artificial intelligence (AI)-enhanced electrocardiogram (ECG) models are designed to detect specific anatomical and functional cardiac abnormalities. Understanding the selectivity of their phenotypic associations is essential to inform their clinical use. Here, we sought to assess whether AI-ECG models function as condition-specific classifiers or broader cardiovascular risk markers. <h4>Met...

Topics

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• Arrhythmias, Cardiac
• Artificial Intelligence
• Death, Sudden, Cardiac
• Genetic Testing
• Machine Learning
• Phenotype

Identifiers and source

Literature Corpus work

e5caff01-1ba4-5ca3-9dba-93a7d8fecc99

DOI

10.1101/2025.07.01.25330665