AIMC Topic: Brain Injuries, Traumatic

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Deep learning: a turning point in acute neurology.

The Lancet. Digital health May 14, 2020
Tomography, X-Ray Computed Deep Learning Brain Injuries, Traumatic Semantics Humans Neurology
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Investigation of Machine Learning Approaches for Traumatic Brain Injury Classification via EEG Assessment in Mice.

Sensors (Basel, Switzerland) Apr 4, 2020
Due to the difficulties and complications in the quantitative assessment of traumatic brain injury (TBI) and its increasing relevance in today's world, robust detection of TBI has become more significant than ever. In this work, we investigate severa...
Male Mice Brain Injuries, Traumatic Mice, Inbred C57BL Electroencephalography Technology Assessment, Biomedical Machine Learning Animals
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Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury.

Journal of clinical epidemiology Mar 20, 2020
OBJECTIVE: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury.
Male Middle Aged Logistic Models Brain Injuries, Traumatic Algorithms Prognosis Female Adult Humans Models, Statistical Machine Learning Decision Making, Computer-Assisted Glasgow Coma Scale
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Unsupervised Machine Learning Reveals Novel Traumatic Brain Injury Patient Phenotypes with Distinct Acute Injury Profiles and Long-Term Outcomes.

Journal of neurotrauma Mar 11, 2020
The heterogeneity of traumatic brain injury (TBI) remains a core challenge for the success of interventional clinical trials. Data-driven approaches for patient stratification may help to identify TBI patient phenotypes during the acute injury period...
Phenotype Female Young Adult Adult Male Humans Brain Injuries, Traumatic Unsupervised Machine Learning Middle Aged Adolescent Time Factors Treatment Outcome
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Endocannabinoid degradation inhibitors ameliorate neuronal and synaptic alterations following traumatic brain injury.

Journal of neurophysiology Jan 8, 2020
Our previous work showed that lateral fluid percussion injury to the sensorimotor cortex (SMC) of anesthetized rats increased neuronal synaptic hyperexcitability in layer 5 (L5) neurons in ex vivo brain slices 10 days postinjury. Furthermore, endocan...
Pyramidal Cells Electrophysiological Phenomena Excitatory Postsynaptic Potentials Sensorimotor Cortex Carbamates Amidohydrolases Succinimides Benzamides Endocannabinoids Benzodioxoles Monoacylglycerol Lipases Machine Learning Brain Injuries, Traumatic Piperazines Animals Piperidines Male Enzyme Inhibitors Rats, Wistar Rats
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Machine learning-based dynamic mortality prediction after traumatic brain injury.

Scientific reports Nov 27, 2019
Our aim was to create simple and largely scalable machine learning-based algorithms that could predict mortality in a real-time fashion during intensive care after traumatic brain injury. We performed an observational multicenter study including adul...
Intracranial Pressure Cerebrovascular Circulation Glasgow Coma Scale Middle Aged Humans ROC Curve Machine Learning Logistic Models Prognosis Brain Injuries, Traumatic Aged Adult Male Intensive Care Units Female
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Anomaly Detection of Moderate Traumatic Brain Injury Using Auto-Regularized Multi-Instance One-Class SVM.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Oct 24, 2019
Detection and quantification of functional deficits due to moderate traumatic brain injury (mTBI) is crucial for clinical decision-making and timely commencement of functional therapy. In this work, we explore magnetoencephalography (MEG) based funct...
Beta Rhythm Glasgow Coma Scale Brain Injuries, Traumatic Automation Neural Pathways Magnetoencephalography Male Adolescent Support Vector Machine Magnetic Resonance Imaging Female Young Adult Adult Sensitivity and Specificity Humans Algorithms Databases, Factual Brain
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Effects of robotic neurorehabilitation through lokomat plus virtual reality on cognitive function in patients with traumatic brain injury: A retrospective case-control study.

The International journal of neuroscience Oct 15, 2019
Traumatic brain injury (TBI) is a clinical condition characterized by damage due to a mechanical physical event, which has a devastating impact on both the patient and his/her family. The purpose of this study is to evaluate the effects of robotic n...
Humans Retrospective Studies Female Adult Male Case-Control Studies Executive Function Attention Psychomotor Performance Neurological Rehabilitation Cognitive Dysfunction Outcome and Process Assessment, Health Care Virtual Reality Brain Injuries, Traumatic Robotics
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Machine Learning to Predict In-Hospital Morbidity and Mortality after Traumatic Brain Injury.

Journal of neurotrauma Sep 18, 2019
Recently, successful predictions using machine learning (ML) algorithms have been reported in various fields. However, in traumatic brain injury (TBI) cohorts, few studies have examined modern ML algorithms. To develop a simple ML model for TBI outco...
Adolescent Child Hospital Mortality Brain Injuries, Traumatic Young Adult Adult Male Middle Aged Prognosis Female Aged Aged, 80 and over Humans Machine Learning
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Comparison between logistic regression and machine learning algorithms on survival prediction of traumatic brain injuries.

Journal of critical care Aug 5, 2019
PURPOSE: To compare twenty-two machine learning (ML) models against logistic regression on survival prediction in severe traumatic brain injury (STBI) patients in a single center study.
Brain Injuries, Traumatic Area Under Curve Female Humans Cross-Sectional Studies Machine Learning Middle Aged Algorithms Logistic Models Prognosis
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