AIMC Topic: Glasgow Coma Scale

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Machine learning model prediction of 6-month functional outcome in elderly patients with intracerebral hemorrhage.

Neurosurgical review May 6, 2022
Spontaneous intracerebral hemorrhage (ICH) has an increasing incidence and a worse outcome in elderly patients. The ability to predict the functional outcome in these patients can be helpful in supporting treatment decisions and establishing prognost...
Retrospective Studies Aged Cerebral Hemorrhage Glasgow Outcome Scale Glasgow Coma Scale Humans Machine Learning Prognosis
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Deep Learning to Predict Outcome in Severe Traumatic Brain Injury.

Radiology Apr 26, 2022
Glasgow Coma Scale Tomography, X-Ray Computed Humans Deep Learning Brain Injuries, Traumatic Prognosis
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Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans.

Radiology Apr 26, 2022
Background After severe traumatic brain injury (sTBI), physicians use long-term prognostication to guide acute clinical care yet struggle to predict outcomes in comatose patients. Purpose To develop and evaluate a prognostic model combining deep lear...
Tomography, X-Ray Computed Adult Male Deep Learning Brain Injuries, Traumatic Humans Prognosis Retrospective Studies Glasgow Coma Scale
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Assessment of an Artificial Intelligence Algorithm for Detection of Intracranial Hemorrhage.

World neurosurgery Mar 5, 2021
BACKGROUND: Immediate and accurate detection of intracranial hemorrhages (ICHs) is essential to provide a good clinical outcome for patients with ICH. Artificial intelligence has the potential to provide this, but the assessment of these methods need...
Humans Artificial Intelligence Algorithms Retrospective Studies Tomography, X-Ray Computed Stroke False Positive Reactions Intracranial Hemorrhages Glasgow Coma Scale Middle Aged Female Cohort Studies Aged Image Processing, Computer-Assisted Sensitivity and Specificity Predictive Value of Tests Male
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Validation of a Machine Learning Brain Electrical Activity-Based Index to Aid in Diagnosing Concussion Among Athletes.

JAMA network open Feb 1, 2021
IMPORTANCE: An objective, reliable indicator of the presence and severity of concussive brain injury and of the readiness for the return to activity has the potential to reduce concussion-related disability.
Electroencephalography Schools Athletes Brain Concussion Male Case-Control Studies Adolescent Universities Athletic Injuries Mental Status and Dementia Tests Glasgow Coma Scale Return to Sport Humans Machine Learning Female Reproducibility of Results Young Adult Prospective Studies Brain
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Predicting the Individual Treatment Effect of Neurosurgery for Patients with Traumatic Brain Injury in the Low-Resource Setting: A Machine Learning Approach in Uganda.

Journal of neurotrauma Dec 14, 2020
Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs). In these low-resource settings, effective triage of patients with TBI-including the decision of whether or not to perform neurosurgery-is critical in op...
Neurosurgical Procedures Glasgow Coma Scale Humans Uganda Treatment Outcome Young Adult Brain Injuries, Traumatic Adult Machine Learning Predictive Value of Tests Middle Aged Male Female Health Resources Adolescent Child
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Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission.

PloS one Nov 17, 2020
A 400-estimator gradient boosting classifier was trained to predict survival probabilities of trauma patients. The National Trauma Data Bank (NTDB) provided 799233 complete patient records (778303 survivors and 20930 deaths) each containing 32 featur...
ROC Curve Humans Heart Rate Glasgow Coma Scale Probability Machine Learning False Positive Reactions Sex Factors Algorithms Injury Severity Score Databases, Factual Risk Reproducibility of Results Wounds and Injuries Hospitalization
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Using Machine Learning to Make Predictions in Patients Who Fall.

The Journal of surgical research Aug 18, 2020
BACKGROUND: As the population ages, the incidence of traumatic falls has been increasing. We hypothesize that a machine learning algorithm can more accurately predict mortality after a fall compared with a standard logistic regression (LR) model base...
Humans Machine Learning Algorithms Female Injury Severity Score Aged Aged, 80 and over Trauma Centers Accidental Falls Retrospective Studies Glasgow Coma Scale ROC Curve Intensive Care Units Adult Decision Trees Male Patient Discharge Middle Aged Length of Stay
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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.
Glasgow Coma Scale Humans Machine Learning Logistic Models Algorithms Brain Injuries, Traumatic Prognosis Models, Statistical Decision Making, Computer-Assisted Female Adult Male Middle Aged
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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...
Middle Aged Female Humans Intracranial Pressure ROC Curve Aged Glasgow Coma Scale Cerebrovascular Circulation Machine Learning Adult Logistic Models Prognosis Male Brain Injuries, Traumatic Intensive Care Units
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