Artificial Intelligence in Cardiovascular Medicine: A Practical Guide for Clinicians and Researchers

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ID: 329665
2026
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Ranked #59 of 80 articles by views in European Heart Journal - Digital Health

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Abstract
Abstract Artificial intelligence (AI) is transforming cardiovascular medicine by extracting clinically relevant patterns from complex digital health data, extending beyond traditional statistical approaches. However, the translation of AI from proof-of-concept studies to routine cardiovascular care remains constrained by methodological, ethical, and regulatory challenges. Key barriers include data quality and representativeness, model generalizability, calibration and clinical utility, interpretability, and the risk of bias amplification. To address this gap, this review synthesizes current evidence on AI applications in cardiology, demystifies foundational machine learning concepts for a clinical audience, and outlines a practical framework for best practices in model development, evaluation, and responsible clinical deployment.
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openalex_W7214181453 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Christian Basile, Alessandro Villaschi, Pasquale Ambrosino, Mario Enrico Canonico, Araz Rawshani, Emanuele Bobbio
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Journal European Heart Journal - Digital Health
Year 2026
DOI
10.1093/ehjdh/ztag153
URL
https://doi.org/10.1093/ehjdh/ztag153
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