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Brain Injuries

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Integrated Multiomics Analysis Identifies a Novel Biomarker Associated with Prognosis in Intracerebral Hemorrhage.

Oxidative medicine and cellular longevity
Existing treatments for intracerebral hemorrhage (ICH) are unable to satisfactorily prevent development of secondary brain injury after ICH and multiple pathological mechanisms are involved in the development of the injury. In this study, we aimed to...

Development and Validation of a Model to Identify Critical Brain Injuries Using Natural Language Processing of Text Computed Tomography Reports.

JAMA network open
IMPORTANCE: Clinical text reports from head computed tomography (CT) represent rich, incompletely utilized information regarding acute brain injuries and neurologic outcomes. CT reports are unstructured; thus, extracting information at scale requires...

Development and External Validation of a Machine Learning Model for the Early Prediction of Doses of Harmful Intracranial Pressure in Patients with Severe Traumatic Brain Injury.

Journal of neurotrauma
Treatment and prevention of elevated intracranial pressure (ICP) is crucial in patients with severe traumatic brain injury (TBI). Elevated ICP is associated with secondary brain injury, and both intensity and duration of an episode of intracranial hy...

Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness.

Journal of neuroengineering and rehabilitation
BACKGROUND: In the past decade, there has been substantial progress in the development of robotic controllers that specify how lower-limb exoskeletons should interact with brain-injured patients. However, it is still an open question which exoskeleto...

Effect of gait distance during robot training on walking independence after acute brain injury.

Assistive technology : the official journal of RESNA
This study aimed to determine whether the distance of gait training using a hybrid assistive limb (HAL) is related to the improvement of walking independence in patients with acute brain injury. This was an exploratory, observational study. Thirty pa...

A Morphologically Individualized Deep Learning Brain Injury Model.

Journal of neurotrauma
The brain injury modeling community has recommended improving model subject specificity and simulation efficiency. Here, we extend an instantaneous (< 1 sec) convolutional neural network (CNN) brain model based on the anisotropic Worcester Head Injur...

Efficient Generation of Pretraining Samples for Developing a Deep Learning Brain Injury Model via Transfer Learning.

Annals of biomedical engineering
The large amount of training samples required to develop a deep learning brain injury model demands enormous computational resources. Here, we study how a transformer neural network (TNN) of high accuracy can be used to efficiently generate pretraini...

Ethical Considerations in Neuroprognostication Following Acute Brain Injury.

Seminars in neurology
Neuroprognostication following acute brain injury (ABI) is a complex process that involves integrating vast amounts of information to predict a patient's likely trajectory of neurologic recovery. In this setting, critically evaluating salient ethical...

Neuromonitoring in the ICU - what, how and why?

Current opinion in critical care
PURPOSE OF REVIEW: We selectively review emerging noninvasive neuromonitoring techniques and the evidence that supports their use in the ICU setting. The focus is on neuromonitoring research in patients with acute brain injury.

Global research evolution and frontier analysis of artificial intelligence in brain injury: A bibliometric analysis.

Brain research bulletin
Research on artificial intelligence for brain injury is currently a prominent area of scientific research. A significant amount of related literature has been accumulated in this field. This study aims to identify hotspots and clarify research resour...