2019/01/01 by Christopher V. Cosgriff, Leo Anthony Celi, David J. Stone · 1 voice · 1 citation
Computer Science · Medicine · #Artificial Intelligence in Healthcare and Education #COVID-19 diagnosis using AI #Machine Learning in Healthcare
paper · pdf · doi:10.1177/1179597219856564
openalex publication_date 2019/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
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.