Critical Care, Critical Data. (June 2019)

• Record Type: Journal Article
• Authors: Cosgriff, Christopher V; Celi, Leo Anthony; Stone, David J
• Is Part Of: Biomedical engineering and computational biology. Volume 10(2019)
• Publication Date: 2019-06
• Subjects: Data analytics -- database -- critical care -- intensive care units -- machine learning; Biomedical engineering -- Periodicals; Computational biology -- Periodicals; Biomedical Engineering; Computational Biology; Biomedical engineering; Computational biology; Electronic journals; Periodicals; Fulltext; Internet Resources; Periodicals; Periodicals; 610.2805
• DOI: 10.1177/1179597219856564
• Languages: English
• ISSNs: 1179-5972

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.