AIMC Topic: Brain Injuries, Traumatic

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Machine learning prediction models for in-hospital postoperative functional outcome after moderate-to-severe traumatic brain injury.

European journal of trauma and emergency surgery : official publication of the European Trauma Society Feb 14, 2024
AIM: This study aims to utilize machine learning (ML) and logistic regression (LR) models to predict surgical outcomes among patients with traumatic brain injury (TBI) based on admission examination, assisting in making optimal surgical treatment dec...
Adult Male Female Aged Brain Injuries, Traumatic Glasgow Outcome Scale Middle Aged Logistic Models Humans Machine Learning Retrospective Studies
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Using Artificial Intelligence to Predict Intracranial Hypertension in Patients After Traumatic Brain Injury: A Systematic Review.

Neurocritical care Jan 11, 2024
Intracranial hypertension (IH) is a key driver of secondary brain injury in patients with traumatic brain injury. Lowering intracranial pressure (ICP) as soon as IH occurs is important, but a preemptive approach would be more beneficial. We systemati...
Humans Intracranial Hypertension Brain Injuries, Traumatic Artificial Intelligence Intracranial Pressure Machine Learning
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Response to Wang et al., (doi: 10.1089/neu.2019.6705).

Journal of neurotrauma Dec 20, 2023
Humans Unsupervised Machine Learning Phenotype Brain Injuries, Traumatic
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Prediction of therapeutic intensity level from automatic multiclass segmentation of traumatic brain injury lesions on CT-scans.

Scientific reports Nov 17, 2023
The prediction of the therapeutic intensity level (TIL) for severe traumatic brain injury (TBI) patients at the early phase of intensive care unit (ICU) remains challenging. Computed tomography images are still manually quantified and then underexplo...
Head Image Processing, Computer-Assisted Brain Injuries, Traumatic Humans Neural Networks, Computer Artificial Intelligence Tomography, X-Ray Computed
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Response to Folweiler KA et al., Unsupervised Machine Learning Reveals Novel Traumatic Brain Injury Patient Phenotypes With Distinct Acute Injury Profiles and Long-Term Outcomes (DOI: 10.1089/neu.2019.6705).

Journal of neurotrauma Oct 18, 2023
Brain Injuries, Traumatic Unsupervised Machine Learning Humans Phenotype
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Mortality prediction using medical time series on TBI patients.

Computer methods and programs in biomedicine Sep 21, 2023
BACKGROUND AND OBJECTIVE: Traumatic Brain Injury (TBI) is one of the leading causes of injury-related mortality in the world, with severe cases reaching mortality rates of 30-40%. It is highly heterogeneous both in causes and consequences making more...
Humans Prognosis Brain Injuries, Traumatic Artificial Intelligence Time Factors Critical Care
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A comparison of performance between a deep learning model with residents for localization and classification of intracranial hemorrhage.

Scientific reports Jun 20, 2023
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...
Intracranial Hemorrhages Tomography, X-Ray Computed Brain Injuries, Traumatic Deep Learning Humans Neurosurgery
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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 Jun 3, 2023
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).
Retrospective Studies Tomography, X-Ray Computed Deep Learning Brain Injuries, Traumatic Humans Hydrocephalus Neuroimaging
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An Empirical Comparison of Explainable Artificial Intelligence Methods for Clinical Data: A Case Study on Traumatic Brain Injury.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 29, 2023
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...
Artificial Intelligence Time Factors Research Personnel Humans Algorithms Brain Injuries, Traumatic
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Machine-learning-based head impact subtyping based on the spectral densities of the measurable head kinematics.

Journal of sport and health science Mar 13, 2023
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...
Brain Injuries, Traumatic Head Machine Learning Biomechanical Phenomena Mouth Protectors Humans
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