Exploring ‘algo-rhythms’ in cardiovascular diseases: a narrative review of the efficacy of using artificial intelligence in coronary artery disease and atrial fibrillation

Saksham Sharma; Simran Bhatia; Aishwar Dixit; Akshaya J. Kumar; Harshal Singla

doi:10.18203/2320-6012.ijrms20242646

Authors

Saksham Sharma Department of Medicine, University of Niš, Niš, Serbia https://orcid.org/0009-0006-6837-4879
Simran Bhatia Department of Medicine, Kasturba Medical College, Manipal, Karnataka, India https://orcid.org/0009-0009-2738-655X
Aishwar Dixit Department of Medicine, Baba Raghav Das Medical College, Gorakhpur, Uttar Pradesh, India https://orcid.org/0000-0002-7271-3785
Akshaya J. Kumar Department of Medicine, M.S. Ramaiah Medical College, Bangalore, Karnataka, India https://orcid.org/0009-0001-4149-1171
Harshal Singla Department of Medicine, Baba Farid University of Health Sciences, Faridkot, Punjab, India https://orcid.org/0009-0002-9106-1185

DOI:

https://doi.org/10.18203/2320-6012.ijrms20242646

Keywords:

Cardiology, Artificial intelligence, Coronary artery disease, Atrial fibrillation, Deep neural networks

Abstract

Recent strides in cardiology have introduced a transformative era by integrating artificial intelligence (AI) into coronary artery disease (CAD) management. This comprehensive review comprehensively explores AI applications in CAD, including diagnosis, screening, risk stratification, treatment assistance, and prognosis. Acknowledging AI's potential to revolutionize CAD care, the review emphasizes understanding current integration and limitations for clinicians and researchers. The manuscript explores the current and potential applications of AI in managing cardiovascular disorders underscoring the developments in cardiovascular care for CAD and atrial fibrillation (AF). The manuscript has been drafted based on scale for the assessment of narrative review articles (SANRA) guidelines to search, compile, contemplate, and extract data. Investigators independently searched PubMed, and Google Scholar following the protocol mentioned in the literature. This manuscript illuminates the evolving landscape of AI in CAD and AF management. While showcasing AI's promise in diagnostic accuracy and treatment strategies, the review emphasizes a cautious yet optimistic approach. The comparison with conventional methods reveals AI's efficacy, signalling a paradigm shift in cardiovascular care. Acknowledging limitations, researchers and clinicians are urged to navigate the integration of AI with discernment. The synthesis of optimism and caution guides the harnessing of AI's transformative potential in advancing cardiovascular healthcare.

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