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Editorial| Volume 404, P1-4, September 15, 2019

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Artificial intelligence in neurocritical care

  • Fawaz Al-Mufti
    Correspondence
    Corresponding author at: Neuroendovascular Surgery and Neurocritical Care Attending, Westchester Medical Center, New York Medical College, 100 Woods Road, Macy Pavilion 1331, Valhalla, NY 10595, United States of America.
    Affiliations
    Departments of Neurosurgery, Westchester Medical Center, New York Medical College, Valhalla, NY, United States of America

    Departments of Neurology, Westchester Medical Center at New York Medical College, Valhalla, NY, United States of America
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  • Vincent Dodson
    Affiliations
    Department of Neurosurgery, Rutgers University, New Jersey Medical School, Newark, NJ, United States of America
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  • James Lee
    Affiliations
    Department of Neurosurgery, Rutgers University, New Jersey Medical School, Newark, NJ, United States of America

    Department of Neurology, Rutgers University, Robert Wood Johnson Medical School, New Brunswick, NJ, United States of America
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  • Ethan Wajswol
    Affiliations
    Department of Neurosurgery, Rutgers University, New Jersey Medical School, Newark, NJ, United States of America
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  • Chirag Gandhi
    Affiliations
    Departments of Neurosurgery, Westchester Medical Center, New York Medical College, Valhalla, NY, United States of America

    Departments of Neurology, Westchester Medical Center at New York Medical College, Valhalla, NY, United States of America
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  • Corey Scurlock
    Affiliations
    Departments of Anesthesiology, Westchester Medical Center at New York Medical College, Valhalla, NY, United States of America

    Departments of Internal Medicine, Westchester Medical Center at New York Medical College, Valhalla, NY, United States of America
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  • Chad Cole
    Affiliations
    Departments of Neurosurgery, Westchester Medical Center, New York Medical College, Valhalla, NY, United States of America
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  • Kiwon Lee
    Affiliations
    Department of Neurosurgery, Rutgers University, New Jersey Medical School, Newark, NJ, United States of America

    Department of Neurology, Rutgers University, Robert Wood Johnson Medical School, New Brunswick, NJ, United States of America
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  • Stephan A. Mayer
    Affiliations
    Department of Neurology, Henry Ford Health System, Detroit, MI, United States of America
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      Abstract

      Background

      Neurocritical care combines the management of extremely complex disease states with the inherent limitations of clinically assessing patients with brain injury. As the management of neurocritical care patients can be immensely complicated, the automation of data-collection and basic management by artificial intelligence systems have garnered interest.

      Methods

      In this opinion article, we highlight the potential artificial intelligence has in monitoring and managing several aspects of neurocritical care, specifically intracranial pressure, seizure monitoring, blood pressure, and ventilation.

      Results

      The two major AI methods of analytical technique currently exist for analyzing critical care data: the model-based method and data driven method. Both of these methods have demonstrated an ability to analyze vast quantities of patient data, and we highlight the ways in which these modalities of artificial intelligence might one day play a role in neurocritical care.

      Conclusions

      While none of these artificial intelligence systems are meant to replace the clinician's judgment, these systems have the potential to reduce healthcare costs and errors or delays in medical management.

      Keywords

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