Why the study?
Clinicians with limited computer science expertise need a better understanding of current artificial intelligence applications in cardiovascular diseases to help integrate algorithms into clinical practice.
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Design
Review
This review highlights the potential of artificial intelligence to accelerate diagnosis, enhance auxiliary tools, improve disease stratification, and predict outcomes across various cardiovascular diseases.
Artificial intelligence (AI), the technique of extracting information from complex database using sophisticated computer algorithms, has incorporated itself in medical field. AI techniques have shown the potential to accelerate the progression of diagnosis and treatment of cardiovascular diseases (CVDs), including heart failure, atrial fibrillation, valvular heart disease, hypertrophic cardiomyopathy, congenital heart disease and so on. In clinical scenario, AI have been proved to apply well in CVD diagnosis, enhance effectiveness of auxiliary tools, disease stratification and typing, and outcome prediction. Deeply developed to capture subtle connections from massive amounts of healthcare data, recent AI algorithms are expected to handle even more complex tasks than traditional methods. The aim of this review is to introduce current applications of AI in CVDs, which may allow clinicians who have limited expertise of computer science to better understand the frontier of the subject and put AI algorithms into clinical practice.
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Sun et al. (2023) studied this question.
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