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Journal of Cardiovascular Translational Research

Erschienen in:

06.05.2020 | Review

Big Data and Atrial Fibrillation: Current Understanding and New Opportunities

verfasst von: Qian-Chen Wang, Zhen-Yu Wang

Erschienen in: Journal of Cardiovascular Translational Research | Ausgabe 6/2020

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Abstract

Atrial fibrillation (AF) is the most common arrhythmia with diverse etiology that remarkably relates to high morbidity and mortality. With the advancements in intensive clinical and basic research, the understanding of electrophysiological and pathophysiological mechanism, as well as treatment of AF have made huge progress. However, many unresolved issues remain, including the core mechanisms and key intervention targets. Big data approach has produced new insights into the improvement of the situation. A large amount of data have been accumulated in the field of AF research, thus using the big data to achieve prevention and precise treatment of AF may be the direction of future development. In this review, we will discuss the current understanding of big data and explore the potential applications of big data in AF research, including predictive models of disease processes, disease heterogeneity, drug safety and development, precision medicine, and the potential source for big data acquisition.

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Titel: Big Data and Atrial Fibrillation: Current Understanding and New Opportunities
verfasst von: Qian-Chen Wang
Zhen-Yu Wang
Publikationsdatum: 06.05.2020
Verlag: Springer US
Erschienen in: Journal of Cardiovascular Translational Research / Ausgabe 6/2020
Print ISSN: 1937-5387
Elektronische ISSN: 1937-5395
DOI: https://doi.org/10.1007/s12265-020-10008-5

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Big Data and Atrial Fibrillation: Current Understanding and New Opportunities

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