AIMC Topic: Cerebral Hemorrhage

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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...

Identification and Validation of Phagocytosis-Regulating Factors as Potential Prognostic and Diagnostic Biomarkers for Intracerebral Hemorrhage Through Single-Cell and Bulk Transcriptomic.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Intracerebral hemorrhage (ICH) is a major cause of death and disability worldwide. Despite treatment advances, reliable prognostic biomarkers are still lacking. While phagocytosis regulation is implicated in ICH pathogenesis, its potential for diagno...

The performance of artificial intelligence in image-based prediction of hematoma enlargement: a systematic review and meta-analysis.

Annals of medicine
BACKGROUND: Accurately predicting hematoma enlargement (HE) is crucial for improving the prognosis of patients with cerebral haemorrhage. Artificial intelligence (AI) is a potentially reliable assistant for medical image recognition. This study syste...

Automated Detection of the Black Hole Sign for Patients with Intracerebral Hemorrhage Using Self-Supervised Learning.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Intracerebral hemorrhage is a devastating form of stroke. Hematoma expansion (HE), growth of the hematoma on interval scans, predicts death and disability. Accurate prediction of HE is crucial for targeted interventions to imp...

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 ...

Evolving Therapeutic Landscape of Intracerebral Hemorrhage: Emerging Cutting-Edge Advancements in Surgical Robots, Regenerative Medicine, and Neurorehabilitation Techniques.

Translational stroke research
Intracerebral hemorrhage (ICH) is the most serious form of stroke and has limited available therapeutic options. As knowledge on ICH rapidly develops, cutting-edge techniques in the fields of surgical robots, regenerative medicine, and neurorehabilit...

Clinical, radiological, and radiomics feature-based explainable machine learning models for prediction of neurological deterioration and 90-day outcomes in mild intracerebral hemorrhage.

BMC medical imaging
BACKGROUND: The risks and prognosis of mild intracerebral hemorrhage (ICH) patients were easily overlooked by clinicians. Our goal was to use machine learning (ML) methods to predict mild ICH patients' neurological deterioration (ND) and 90-day progn...