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<p>Electrocardiographic artificial intelligence (ECG-AI) uses AI-based algorithms to analyze ECGs. Recent literature has revealed the untapped potential of ECG beyond traditional diagnostics. ECG-AI is now used not only to detect arrhythmias but also to assess risk and identify both cardiovascular and non-cardiovascular conditions. This perspective article summarizes evidence from published literature to support the conclusion that ECG-AI models are highly generalizable and have the potential to revolutionize healthcare.</p>

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Generalizability of electrocardiographic artificial intelligence

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月15日

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  • Ibrahim Karabayir,
  • Oguz Akbilgic

摘要

Electrocardiographic artificial intelligence (ECG-AI) uses AI-based algorithms to analyze ECGs. Recent literature has revealed the untapped potential of ECG beyond traditional diagnostics. ECG-AI is now used not only to detect arrhythmias but also to assess risk and identify both cardiovascular and non-cardiovascular conditions. This perspective article summarizes evidence from published literature to support the conclusion that ECG-AI models are highly generalizable and have the potential to revolutionize healthcare.