AIMC Topic: Brain Injuries, Traumatic
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Latent Trajectories of Cerebral Perfusion Pressure and Risk Prediction Models Among Patients with Traumatic Brain Injury: Based on an Interpretable Artificial Neural Network.
World neurosurgery
Sep 13, 2024
OBJECTIVE: This study aimed to characterize long-term cerebral perfusion pressure (CPP) trajectory in traumatic brain injury (TBI) patients and construct an interpretable prediction model to assess the risk of unfavorable CPP evolution patterns.
Letter to Editor: Comment on, "Development of predictive model for the neurological deterioration among mild traumatic brain injury patients using machine learning algorithms".
Neurosurgical review
Sep 6, 2024
Development of a System for Predicting Hospitalization Time for Patients With Traumatic Brain Injury Based on Machine Learning Algorithms: User-Centered Design Case Study.
JMIR human factors
Aug 30, 2024
BACKGROUND: Currently, the treatment and care of patients with traumatic brain injury (TBI) are intractable health problems worldwide and greatly increase the medical burden in society. However, machine learning-based algorithms and the use of a larg...
Development of predictive model for the neurological deterioration among mild traumatic brain injury patients using machine learning algorithms.
Neurosurgical review
Aug 28, 2024
BACKGROUND: Mild traumatic brain injury (mTBI) comprises a majority of traumatic brain injury (TBI) cases. While some mTBI would suffer neurological deterioration (ND) and therefore have poorer prognosis. This study was designed to develop the predic...
AI-Based Denoising of Head Impact Kinematics Measurements With Convolutional Neural Network for Traumatic Brain Injury Prediction.
IEEE transactions on bio-medical engineering
Aug 21, 2024
OBJECTIVE: Wearable devices are developed to measure head impact kinematics but are intrinsically noisy because of the imperfect interface with human bodies. This study aimed to improve the head impact kinematics measurements obtained from instrument...
Predictive Models of Long-Term Outcome in Patients with Moderate to Severe Traumatic Brain Injury are Biased Toward Mortality Prediction.
Neurocritical care
Aug 13, 2024
BACKGROUND: The prognostication of long-term functional outcomes remains challenging in patients with traumatic brain injury (TBI). Our aim was to demonstrate that intensive care unit (ICU) variables are not efficient to predict 6-month functional ou...
Accuracy and time efficiency of a novel deep learning algorithm for Intracranial Hemorrhage detection in CT Scans.
La Radiologia medica
Aug 9, 2024
PURPOSE: To evaluate a deep learning-based pipeline using a Dense-UNet architecture for the assessment of acute intracranial hemorrhage (ICH) on non-contrast computed tomography (NCCT) head scans after traumatic brain injury (TBI).
Evaluating performance of a near-infrared-spectroscopy-based and machine-learning-powered bio-optical sensitivity parameters in identifying intracranial hemorrhages in TBI across different age-groups.
Brain injury
Jul 31, 2024
PRIMARY OBJECTIVE: To evaluate the accuracy of an innovative machine-learning-powered near-infrared spectroscopy (mNIRS)-based bio-optical sensitivity parameters, namely specific tissue optical index (STOI) and intracranial tissue optical index (ITOI...
Brain Injuries, Traumatic
Double-Blind Method
Intracranial Hemorrhages
Sensitivity and Specificity
Child, Preschool
Aged
Humans
Spectroscopy, Near-Infrared
Cross-Sectional Studies
Child
Adolescent
Machine Learning
Aged, 80 and over
Male
Age Factors
Young Adult
Prospective Studies
Middle Aged
Adult
Female
Machine learning for automating subjective clinical assessment of gait impairment in people with acquired brain injury - a comparison of an image extraction and classification system to expert scoring.
Journal of neuroengineering and rehabilitation
Jul 23, 2024
BACKGROUND: Walking impairment is a common disability post acquired brain injury (ABI), with visually evident arm movement abnormality identified as negatively impacting a multitude of psychological factors. The International Classification of Functi...
Deriving Automated Device Metadata From Intracranial Pressure Waveforms: A Transforming Research and Clinical Knowledge in Traumatic Brain Injury ICU Physiology Cohort Analysis.
Critical care explorations
Jul 16, 2024
IMPORTANCE: Treatment for intracranial pressure (ICP) has been increasingly informed by machine learning (ML)-derived ICP waveform characteristics. There are gaps, however, in understanding how ICP monitor type may bias waveform characteristics used ...
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