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Related Experiment Video

Updated: Oct 5, 2025

A Detailed Protocol for Physiological Parameters Acquisition and Analysis in Neurosurgical Critical Patients
05:01

A Detailed Protocol for Physiological Parameters Acquisition and Analysis in Neurosurgical Critical Patients

Published on: October 17, 2017

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Big data and predictive analytics in neurocritical care.

Ayham Alkhachroum1, Julie Kromm2,3,4, Michael A De Georgia5

  • 1Miller School of Medicine, Neurocritical Care Division, Department of Neurology, University of Miami, Miami, FL, 33146, USA.

Current Neurology and Neuroscience Reports
|January 26, 2022
PubMed
Summary

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This review explores predictive data and workflows for managing critically ill neurological patients. It highlights multimodal monitoring and data management for improved neurocritical care decision support.

Area of Science:

  • Neuroscience
  • Critical Care Medicine
  • Data Science

Background:

  • Intensive care units (ICUs) generate vast amounts of data, particularly in neurocritical care.
  • Multimodal monitoring in neurocritical care aims to prevent secondary brain injury by analyzing complex physiological data.
  • The goal is to advance personalized medicine through sophisticated data analysis.

Purpose of the Study:

  • To describe predictive data and workflows in intensive care units for managing neurologically ill patients.
  • To highlight the application of multimodal monitoring in neurocritical care.
  • To discuss information management strategies for neurocritical care data.

Main Methods:

  • Review of predictive data used in neurocritical care.
  • Description of data acquisition, wrangling, analysis, and visualization techniques.
Keywords:
MonitoringNeurocritical carePrecision medicinePredictive data

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Last Updated: Oct 5, 2025

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  • Focus on multimodal monitoring of cerebral hemodynamics, brain oxygenation, metabolism, and electrophysiology.

    • Main Results:

    • Neurocritical care units are data-rich environments requiring advanced data management.
    • Multimodal monitoring provides complex, dynamic interactions crucial for personalized medicine.
    • Predictive data aids in diagnosing, treating, and prognosing neurological conditions.

    Conclusions:

    • Effective information management is essential for optimizing decision support systems in neurocritical care.
    • Integrating multimodal monitoring data can lead to improved patient outcomes.
    • The application of Big Data principles is transforming neurocritical care practices.