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2000
Volume 21, Issue 4
  • ISSN: 1573-403X
  • E-ISSN: 1875-6557

Abstract

Background

At a critical juncture in the ongoing fight against cardiovascular disease (CVD), healthcare professionals are striving for more informed and expedited decision-making. Artificial intelligence (AI) promises to be a guiding light in this endeavor. The diagnosis of coronary artery disease has now become non-invasive and convenient, while wearable devices excel at promptly detecting life-threatening arrhythmias and treatments for heart failure.

Objective

This study aimed to highlight the applications of AI in cardiology with a particular focus on arrhythmias and its potential impact on healthcare for all through careful implementation and constant research efforts.

Methods

An extensive search strategy was implemented. The search was conducted in renowned electronic medical databases, including Medline, PubMed, Cochrane Library, and Google Scholar. Artificial Intelligence, cardiovascular diseases, arrhythmias, machine learning, and convolutional neural networks in cardiology were used as keywords for the search strategy.

Results

A total of 6876 records were retrieved from different electronic databases. Duplicates (N = 1356) were removed, resulting in 5520 records for screening. Based on predefined inclusion and exclusion criteria, 4683 articles were excluded. Following the full-text screening of the remaining 837 articles, a further 637 were excluded. Ultimately, 200 studies were included in this review.

Conclusion

AI represents not just a development but a cutting-edge force propelling the next evolution of cardiology. With its capacity to make precise predictions, facilitate non-invasive diagnosis, and personalize therapies, AI holds the potential to save lives and enhance healthcare quality on a global scale.

© 2025 Bentham Science Publishers
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Artificial Intelligence in the Heart of Medicine: A Systematic Approach to Transforming Arrhythmia Care with Intelligent Systems
Curr. Cardiol. Rev. 21, E1573403X334095 (2025); https://doi.org/10.2174/011573403X334095241205041550
/content/journals/ccr/10.2174/011573403X334095241205041550
/content/journals/ccr/10.2174/011573403X334095241205041550
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  • Article Type:     Review Article
Keyword(s): arrhythmias; Artificial intelligence; cardiology; cardiovascular disease; heart failure; machine learning

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