ReviewFrontiers in neurology2020
Machine Learning Applications in the Neuro ICU: A Solution to Big Data Mayhem?
Review in Frontiers in neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Binary Classification of Consciousness Using Cerebral Blood Flow and EEG Features.Neurocritical care · 2026Article
- JinhuaNSICU, an open accessible Neurosurgical Intensive Care Database.Scientific data · 2025Article
- Determinants and predictors of early re-admission of patients with hyperglycemic crises: a machine learning-based analysis.Journal of diabetes and metabolic disorders · 2025Article
- Article
- Early prediction of mortality upon intensive care unit admission.BMC medical informatics and decision making · 2024Article
- From bed to bench and back again: Challenges facing deployment of intracranial pressure data analysis in clinical environments.Brain & spine · 2024Review
- Sub-Scalp Implantable Telemetric EEG (SITE) for the Management of Neurological and Behavioral Disorders beyond Epilepsy.Brain sciences · 2023Review
- Review
- Developing DELPHI expert consensus rules for a digital twin model of acute stroke care in the neuro critical care unit.BMC neurology · 2023Article
- Convergence of Artificial Intelligence and Neuroscience towards the Diagnosis of Neurological Disorders-A Scoping Review.Sensors (Basel, Switzerland) · 2023Article
- Interoperable and explainable machine learning models to predict morbidity and mortality in acute neurological injury in the pediatric intensive care unit: secondary analysis of the TOPICC study.Frontiers in pediatrics · 2023Article
- Development and Trends in Artificial Intelligence in Critical Care Medicine: A Bibliometric Analysis of Related Research over the Period of 2010-2021.Journal of personalized medicine · 2022Article
- Clinico-biological markers for the prognosis of status epilepticus in adults.Journal of neurology · 2022Article
- Demystifying the Black Box: The Importance of Interpretability of Predictive Models in Neurocritical Care.Neurocritical care · 2022Article
- Adult Critical Care Electroencephalography Monitoring for Seizures: A Narrative Review.Frontiers in neurology · 2022Review
- Predictive modeling in neurocritical care using causal artificial intelligence.World journal of critical care medicine · 2021Review
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The neurological ICU (neuro ICU) often suffers from significant limitations due to scarce resource availability for their neurocritical care patients. Neuro ICU patients require frequent neurological evaluations, continuous monitoring of various physiological parameters, frequent imaging, and routine lab testing. This amasses large amounts of data specific to each patient. Neuro ICU teams are often overburdened by the resulting complexity of data for each patient. Machine Learning algorithms (ML), are uniquely capable of interpreting high-dimensional datasets that are too difficult for humans to comprehend. Therefore, the application of ML in the neuro ICU could alleviate the burden of analyzing big datasets for each patient. This review serves to (1) briefly summarize ML and compare the different types of MLs, (2) review recent ML applications to improve neuro ICU management and (3) describe the future implications of ML to neuro ICU management.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.