AIMC Topic: Glasgow Coma Scale

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Phenotypes of Patients with Intracerebral Hemorrhage, Complications, and Outcomes.

Neurocritical care
BACKGROUND: The objective of this study was to define clinically meaningful phenotypes of intracerebral hemorrhage (ICH) using machine learning.

Enhancing Outcome Prediction in Intracerebral Hemorrhage Through Deep Learning: A Retrospective Multicenter Study.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to employ deep learning techniques to analyze and validate an automatic prognostic biomarker for predicting outcomes following intracerebral hemorrhage (ICH).

Predicting the Severity and Discharge Prognosis of Traumatic Brain Injury Based on Intracranial Pressure Data Using Machine Learning Algorithms.

World neurosurgery
OBJECTIVE: This study aimed to explore the potential of employing machine learning algorithms based on intracranial pressure (ICP), ICP-derived parameters, and their complexity to predict the severity and short-term prognosis of traumatic brain injur...

Upper gastrointestinal haemorrhage patients' survival: A causal inference and prediction study.

European journal of clinical investigation
BACKGROUND: Upper gastrointestinal (GI) bleeding is a common medical emergency. This study aimed to develop models to predict critically ill patients with upper GI bleeding in-hospital and 30-day survival, identify the correlation factor and infer th...

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

Neurosurgical review
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...

Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans.

Radiology
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...

Assessment of an Artificial Intelligence Algorithm for Detection of Intracranial Hemorrhage.

World neurosurgery
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...

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
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...