AIMC Topic: Brain Injuries, Traumatic

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Using trauma registry data to predict prolonged mechanical ventilation in patients with traumatic brain injury: Machine learning approach.

PloS one Jul 8, 2020
OBJECTIVES: We aimed to build a machine learning predictive model to predict the risk of prolonged mechanical ventilation (PMV) for patients with Traumatic Brain Injury (TBI).
Logistic Models Treatment Outcome Brain Injuries, Traumatic Registries Models, Biological Young Adult Adult Male Respiration, Artificial Humans Machine Learning Prognosis Female
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Prediction of in-hospital mortality in patients with post traumatic brain injury using National Trauma Registry and Machine Learning Approach.

Scandinavian journal of trauma, resuscitation and emergency medicine May 27, 2020
BACKGROUND: The use of machine learning techniques to predict diseases outcomes has grown significantly in the last decade. Several studies prove that the machine learning predictive techniques outperform the classical multivariate techniques. We aim...
Humans Machine Learning Registries Multivariate Analysis Middle Aged Female Hospital Mortality Adult Brain Injuries, Traumatic Sensitivity and Specificity Area Under Curve Male
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Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study.

The Lancet. Digital health May 14, 2020
BACKGROUND: CT is the most common imaging modality in traumatic brain injury (TBI). However, its conventional use requires expert clinical interpretation and does not provide detailed quantitative outputs, which may have prognostic importance. We aim...
Deep Learning Adolescent Child Brain Injuries, Traumatic Young Adult Adult Male Middle Aged Europe Radiographic Image Interpretation, Computer-Assisted Humans Semantics Brain Reproducibility of Results Aged Aged, 80 and over Tomography, X-Ray Computed Female
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Deep learning: a turning point in acute neurology.

The Lancet. Digital health May 14, 2020
Tomography, X-Ray Computed Humans Deep Learning Brain Injuries, Traumatic Semantics 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...
Machine Learning Animals Mice Male Brain Injuries, Traumatic Mice, Inbred C57BL Electroencephalography Technology Assessment, Biomedical
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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.
Algorithms Prognosis Female Adult Humans Machine Learning Models, Statistical Decision Making, Computer-Assisted Glasgow Coma Scale Male Middle Aged Logistic Models Brain Injuries, Traumatic
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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...
Treatment Outcome Brain Injuries, Traumatic Unsupervised Machine Learning Male Middle Aged Adolescent Time Factors Phenotype Female Young Adult Adult Humans
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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...
Animals Male Rats, Wistar Machine Learning Benzamides Pyramidal Cells Electrophysiological Phenomena Excitatory Postsynaptic Potentials Benzodioxoles Monoacylglycerol Lipases Sensorimotor Cortex Endocannabinoids Enzyme Inhibitors Carbamates Amidohydrolases Succinimides Rats Brain Injuries, Traumatic Piperazines Piperidines
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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...
Prognosis Intensive Care Units Female Aged Humans Machine Learning Logistic Models Brain Injuries, Traumatic Intracranial Pressure Cerebrovascular Circulation Glasgow Coma Scale Adult Male Middle Aged ROC Curve
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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...
Male Beta Rhythm Adolescent Glasgow Coma Scale Support Vector Machine Female Magnetic Resonance Imaging Young Adult Brain Injuries, Traumatic Adult Humans Automation Algorithms Neural Pathways Databases, Factual Sensitivity and Specificity Magnetoencephalography Brain
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