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Abstract
Artificial intelligence offers the potential for transformational advancement in cardiovascular
care delivery, yet practical applications of this technology have yet to be embedded
in clinical workflows and systems. Recent advances in machine learning algorithms
and accessibility to big data sources have created the ability for software to solve
highly specialized problems outside of health care, such as autonomous driving, speech
recognition, and game playing (chess and Go), at superhuman efficiency previously
not thought possible. To date, high-order cognitive problems in cardiovascular research
such as differential diagnosis, treatment options, and clinical risk stratification
have been difficult to address at scale with artificial intelligence. The practical
application of artificial intelligence in the underlying operational processes in
the delivery of cardiac care may be more amenable where adoption has great potential
to fundamentally transform care delivery while maintaining the core quality and service
that our patients demand. In this article, we provide an overview on how these artificial
intelligence platforms can be implemented to improve the operational delivery of care
for patients with cardiovascular disease.