Big Data in Cardiovascular Disease
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Purpose of Review
Cardiovascular diseases exert a wide-reaching epidemiological impact as the number one cause of death worldwide. Emerging technologies such as big data and artificial intelligence (AI) are poised to significantly change the field of cardiology. However, their applications are still emerging. We aimed to define the role of big data and AI in cardiovascular disease with a focus on research.
There are zettabyte levels (1021 bytes) of big data in the US that can be directed towards healthcare research. There are applications of big data analytics already being put to use with genomics, heart failure readmissions, echocardiography, and many other areas within cardiology.
We profile in this paper an extensive listing of various datasets used throughout the globe to study big data. Within cardiology, there is tremendous potential for the application of big data analytics in personalized patient care; however, they still require validation.
KeywordsCardiology Cardiovascular disease Big data Machine learning Artificial intelligence
Compliance with Ethical Standards
Conflict of Interest
Fabio V. Lima and Regina Druz each declare no potential conflicts of interest. Raymond Russell reports personal fees from ResTORbio, outside the submitted work. His spouse is employed by ResTORbio and also receives stock options. The company is developing novel drugs to treat pulmonary infections as well as Parkinson’s disease and therefore not related to the content of this manuscript.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by the author.
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
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