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Artificial intelligence (AI) applied to electrocardiography (ECG) is transforming the landscape of cardiovascular disease diagnosis and management. AI-ECG systems enhance the identification of heart diseases, including heart failure, atrial fibrillation, and coronary artery disease, by providing timely and accurate predictions. Notably, AI algorithms have been developed to detect conditions such as reduced left ventricular ejection fraction (LVEF) and atrial fibrillation, achieving high diagnostic performance. Additionally, AI-ECG platforms enable early identification of high-risk patients, improving clinical outcomes and reducing mortality. Despite these advancements, challenges remain in explainability, regulatory compliance, and external validation. The future potential of AI-ECG includes integration into prognostic assessment and the use of wearables for widespread screening, offering a promising avenue for personalized medicine and early intervention.

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Electrocardiography: How Artificial Intelligence Can Make a Diagnosis

  • 章节

  • 发表日期：

    2025年

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  • Andrea Saglietto,
  • Luca Nissardi,
  • Gaetano Maria De Ferrari

摘要

Artificial intelligence (AI) applied to electrocardiography (ECG) is transforming the landscape of cardiovascular disease diagnosis and management. AI-ECG systems enhance the identification of heart diseases, including heart failure, atrial fibrillation, and coronary artery disease, by providing timely and accurate predictions. Notably, AI algorithms have been developed to detect conditions such as reduced left ventricular ejection fraction (LVEF) and atrial fibrillation, achieving high diagnostic performance. Additionally, AI-ECG platforms enable early identification of high-risk patients, improving clinical outcomes and reducing mortality. Despite these advancements, challenges remain in explainability, regulatory compliance, and external validation. The future potential of AI-ECG includes integration into prognostic assessment and the use of wearables for widespread screening, offering a promising avenue for personalized medicine and early intervention.