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Brain Injuries, Traumatic

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Ketofol as an Anesthetic Agent in Patients With Isolated Moderate to Severe Traumatic Brain Injury: A Prospective, Randomized Double-blind Controlled Trial.

Journal of neurosurgical anesthesiology
BACKGROUND: The effects of ketofol (propofol and ketamine admixture) on systemic hemodynamics and outcomes in patients undergoing emergency decompressive craniectomy for traumatic brain injury (TBI) are unknown and explored in this study.

An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain Injury.

AMIA ... Annual Symposium proceedings. AMIA Symposium
A longstanding challenge surrounding deep learning algorithms is unpacking and understanding how they make their decisions. Explainable Artificial Intelligence (XAI) offers methods to provide explanations of internal functions of algorithms and reaso...

Automated identification and quantification of traumatic brain injury from CT scans: Are we there yet?

Medicine
BACKGROUND: The purpose of this study was to conduct a systematic review for understanding the availability and limitations of artificial intelligence (AI) approaches that could automatically identify and quantify computed tomography (CT) findings in...

A Machine Learning-Based Approach to Predict Prognosis and Length of Hospital Stay in Adults and Children With Traumatic Brain Injury: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: The treatment and care of adults and children with traumatic brain injury (TBI) constitute an intractable global health problem. Predicting the prognosis and length of hospital stay of patients with TBI may improve therapeutic effects and...

An end-end deep learning framework for lesion segmentation on multi-contrast MR images-an exploratory study in a rat model of traumatic brain injury.

Medical & biological engineering & computing
Traumatic brain injury (TBI) engenders traumatic necrosis and penumbra-areas of secondary neural injury which are crucial targets for therapeutic interventions. Segmenting manually areas of ongoing changes like necrosis, edema, hematoma, and inflamma...

Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics.

Journal of sport and health science
BACKGROUND: Traumatic brain injury can be caused by head impacts, but many brain injury risk estimation models are not equally accurate across the variety of impacts that patients may undergo, and the characteristics of different types of impacts are...

A comparison of performance between a deep learning model with residents for localization and classification of intracranial hemorrhage.

Scientific reports
Intracranial hemorrhage (ICH) from traumatic brain injury (TBI) requires prompt radiological investigation and recognition by physicians. Computed tomography (CT) scanning is the investigation of choice for TBI and has become increasingly utilized un...

Validation of a deep learning model for traumatic brain injury detection and NIRIS grading on non-contrast CT: a multi-reader study with promising results and opportunities for improvement.

Neuroradiology
PURPOSE: This study aimed to assess and externally validate the performance of a deep learning (DL) model for the interpretation of non-contrast computed tomography (NCCT) scans of patients with suspicion of traumatic brain injury (TBI).