Big data and predictive analytics in neurocritical care
- PMID: 35080751
- DOI: 10.1007/s11910-022-01167-w
Big data and predictive analytics in neurocritical care
Abstract
Purpose of review: To describe predictive data and workflow in the intensive care unit when managing neurologically ill patients.
Recent findings: In the era of Big Data in medicine, intensive critical care units are data-rich environments. Neurocritical care adds another layer of data with advanced multimodal monitoring to prevent secondary brain injury from ischemia, tissue hypoxia, and a cascade of ongoing metabolic events. A step closer toward personalized medicine is the application of multimodal monitoring of cerebral hemodynamics, bran oxygenation, brain metabolism, and electrophysiologic indices, all of which have complex and dynamic interactions. These data are acquired and visualized using different tools and monitors facing multiple challenges toward the goal of the optimal decision support system. In this review, we highlight some of the predictive data used to diagnose, treat, and prognosticate the neurologically ill patients. We describe information management in neurocritical care units including data acquisition, wrangling, analysis, and visualization.
Keywords: Monitoring; Neurocritical care; Precision medicine; Predictive data.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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