Critical Care, Critical Data.

IF 2.3 Q3 ENGINEERING, BIOMEDICAL
Biomedical Engineering and Computational Biology Pub Date : 2019-06-12 eCollection Date: 2019-01-01 DOI:10.1177/1179597219856564
Christopher V Cosgriff, Leo Anthony Celi, David J Stone
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引用次数: 30

Abstract

As big data, machine learning, and artificial intelligence continue to penetrate into and transform many facets of our lives, we are witnessing the emergence of these powerful technologies within health care. The use and growth of these technologies has been contingent on the availability of reliable and usable data, a particularly robust resource in critical care medicine where continuous monitoring forms a key component of the infrastructure of care. The response to this opportunity has included the development of open databases for research and other purposes; the development of a collaborative form of clinical data science intended to fully leverage these data resources, and the creation of data-driven applications for purposes such as clinical decision support. Most recently, data levels have reached the thresholds required for the development of robust artificial intelligence features for clinical purposes. The systematic capture and analysis of clinical data in both individuals and populations allows us to begin to move toward precision medicine in the intensive care unit (ICU). In this perspective review, we examine the fundamental role of data as we present the current progress that has been made toward an artificial intelligence (AI)-supported, data-driven precision critical care medicine.

重症监护,关键数据。
随着大数据、机器学习和人工智能继续渗透并改变我们生活的许多方面,我们正在见证这些强大的技术在医疗保健领域的出现。这些技术的使用和增长取决于可靠和可用数据的可用性,这是重症监护医学中一种特别强大的资源,持续监测是护理基础设施的关键组成部分。对这一机会的回应包括开发用于研究和其他目的的开放数据库;开发旨在充分利用这些数据资源的临床数据科学合作形式,并创建用于临床决策支持等目的的数据驱动应用程序。最近,数据水平已经达到开发用于临床目的的强大人工智能功能所需的阈值。对个人和人群临床数据的系统捕获和分析使我们能够开始在重症监护室(ICU)转向精准医疗。在这篇前瞻性综述中,我们研究了数据的基本作用,介绍了目前在人工智能(AI)支持、数据驱动的精准重症医学方面取得的进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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