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June 12, 2026International Journal of CardiologyOpen Access

A scoping review on aging and cardiovascular diseases - Molecular mediators and artificial intelligence-based advanced diagnostic methods

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Authors

ASAntonio M. SudosoLCLorenzo CiarpagliniDSDiego Scuppa

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Overview

Scoping review evaluates AI-derived biological age's impact on cardiovascular risk in aging populations, suggesting promising biomarkers.

Key Points

  • To synthesize evidence on AI-derived biological age and its relation to cardiovascular outcomes, emphasizing its potential for risk prediction.
  • Reviewed studies from PubMed and Scopus published between 2019 and 2025.
  • Included original research on AI estimating biological age in human participants.
  • Data extraction focused on study design, AI methods, biological age metrics, and cardiovascular endpoints.
  • AI-derived biological age consistently outperformed chronological age in risk prediction.
  • Deep learning models revealed an age gap linked to higher risks of heart failure, atrial fibrillation, and stroke.
  • Explainable AI techniques identified key ECG features influencing biological age predictions.

Cite This Study

Sudoso et al. (2026) studied this question.

synapsesocial.com/papers/6a2ba1ca8101cf8926f01035https://doi.org/10.1016/j.ijcard.2026.134615
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Also Consider

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  1. 1Artificial intelligence approaches in biological age prediction: current status and challenges2026
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  5. 5Biological Cardiovascular Age Derived from Coronary CTA Reports Using a Large Language Model: A Novel Predictor of Major Adverse Cardiovascular Events?2026