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September 5, 2025CirculationOpen Access

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

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Authors

PCPhilip M. CroonLDLovedeep Singh DhingraDBDhruva Biswas

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Overview

Observational analysis shows AI-ECG models predict multiple cardiovascular conditions, suggesting broader applicability.

Key Points

  • AI-ECG models are linked to various cardiovascular phenotypes, demonstrating their predictive potential.
  • Odds ratios for AI-ECG models ranged from 2.16 to 4.41, indicating significant associations with cardiovascular conditions.
  • Six AI-ECG models were assessed using logistic regression and Cox regression to evaluate condition-specific versus broader risk predictions.
  • These findings support the use of AI-ECG tools as cardiovascular biomarkers rather than just diagnostic tools.

Cite This Study

Croon et al. (2025) studied this question.

synapsesocial.com/papers/68c239e5b210217d6477e87fhttps://doi.org/10.1161/circulationaha.125.076279
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