AIMC Topic: Cerebral Hemorrhage

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Improving the Accuracy of Scores to Predict Gastrostomy after Intracerebral Hemorrhage with Machine Learning.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: Gastrostomy placement after intracerebral hemorrhage indicates the need for continued medical care and predicts patient dependence. Our objective was to determine the optimal machine learning technique to predict gastrostomy.

A user-guided tool for semi-automated cerebral microbleed detection and volume segmentation: Evaluating vascular injury and data labelling for machine learning.

NeuroImage. Clinical
BACKGROUND AND PURPOSE: With extensive research efforts in place to address the clinical relevance of cerebral microbleeds (CMBs), there remains a need for fast and accurate methods to detect and quantify CMB burden. Although some computer-aided dete...

Prediction of Hemorrhagic Transformation Severity in Acute Stroke From Source Perfusion MRI.

IEEE transactions on bio-medical engineering
OBJECTIVE: Hemorrhagic transformation (HT) is the most severe complication of reperfusion therapy in acute ischemic stroke (AIS) patients. Management of AIS patients could benefit from accurate prediction of upcoming HT. While prediction of HT occurr...

Spontaneous Intraventricular Hemorrhage: When Should Intraventricular tPA Be Considered?

Seminars in respiratory and critical care medicine
Spontaneous intracerebral hemorrhage (ICH) is the most common cause of intraventricular hemorrhage (IVH) in adults. Complicating approximately 40% of ICH cases, IVH adds to the morbidity and mortality of this often fatal form of stroke. It is also a ...

Prognosticating Functional Outcome After Intracerebral Hemorrhage: The ICHOP Score.

World neurosurgery
BACKGROUND: The morbidity, mortality, and monetary cost associated with intracerebral hemorrhage (ICH) is devastatingly high. Several scoring systems have been proposed to prognosticate outcomes after ICH, although the original ICH Score is still the...

Automatic Detection of Cerebral Microbleeds From MR Images via 3D Convolutional Neural Networks.

IEEE transactions on medical imaging
Cerebral microbleeds (CMBs) are small haemorrhages nearby blood vessels. They have been recognized as important diagnostic biomarkers for many cerebrovascular diseases and cognitive dysfunctions. In current clinical routine, CMBs are manually labelle...

Genetic Risk Scores in Stroke Research and Care.

Stroke
Stroke remains a leading cause of death and disability worldwide. While well-established risk factors play a major role, genetic predisposition is a crucial determinant of stroke susceptibility, with heritability estimates up to 39% for ischemic stro...

Deep learning-based clinical decision support system for intracerebral hemorrhage: an imaging-based AI-driven framework for automated hematoma segmentation and trajectory planning.

Neurosurgical focus
OBJECTIVE: Intracerebral hemorrhage (ICH) remains a critical neurosurgical emergency with high mortality and long-term disability. Despite advancements in minimally invasive techniques, procedural precision remains limited by hematoma complexity and ...