NYMC Faculty Publications
Machine Learning and Artificial Intelligence in Neurocritical Care: A Specialty-Wide Disruptive Transformation or a Strategy for Success
DOI
10.1007/s11910-019-0998-8
Journal Title
Current Neurology and Neuroscience Reports
First Page
89
Document Type
Article
Publication Date
November 2019
Department
Neurosurgery
Abstract
PURPOSE OF REVIEW: Neurocritical care combines the complexity of both medical and surgical disease states with the inherent limitations of assessing patients with neurologic injury. Artificial intelligence (AI) has garnered interest in the basic management of these complicated patients as data collection becomes increasingly automated. RECENT FINDINGS: In this opinion article, we highlight the potential AI has in aiding the clinician in several aspects of neurocritical care, particularly in monitoring and managing intracranial pressure, seizures, hemodynamics, and ventilation. The model-based method and data-driven method are currently the two major AI methods for analyzing critical care data. Both are able to analyze the vast quantities of patient data that are accumulated in the neurocritical care unit. AI has the potential to reduce healthcare costs, minimize delays in patient management, and reduce medical errors. However, these systems are an aid to, not a replacement for, the clinician's judgment.
Recommended Citation
Al-Mufti, F., Kim, M., Dodson, V., Sursal, T., Bowers, C., Cole, C., Scurlock, C., Becker, C., Gandhi, C., & Mayer, S. (2019). Machine Learning and Artificial Intelligence in Neurocritical Care: A Specialty-Wide Disruptive Transformation or a Strategy for Success. Current Neurology and Neuroscience Reports, 19 (11), 89. https://doi.org/10.1007/s11910-019-0998-8