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Cerebral Hemorrhage

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Efficacy and Safety of Chinese Herbal Medicine in Patients with Acute Intracerebral Hemorrhage: Protocol for a Randomized Placebo-Controlled Double-Blinded Multicenter Trial.

Cerebrovascular diseases (Basel, Switzerland) 39250890
INTRODUCTION: The popular traditional Chinese medicine (TCM) compound FYTF-919 (Zhong Feng Xing Nao prescription) may improve outcome from acute intracerebral hemorrhage (ICH) through effects on brain edema, hematoma absorption, and the immune system...
Acute Disease Adult Aged Cerebral Hemorrhage China Disability Evaluation Double-Blind Method Drugs, Chinese Herbal Female Functional Status Humans Male Middle Aged Multicenter Studies as Topic Prospective Studies Randomized Controlled Trials as Topic Recovery of Function Time Factors Treatment Outcome
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Advancements in prognostic markers and predictive models for intracerebral hemorrhage: from serum biomarkers to artificial intelligence models.

Neurosurgical review 39083096
Intracerebral hemorrhage (ICH) is a severe form of stroke with high morbidity and mortality, accounting for 10-15% of all strokes globally. Recent advancements in prognostic biomarkers and predictive models have shown promise in enhancing the predict...
Artificial Intelligence Biomarkers Cerebral Hemorrhage Humans Machine Learning Prognosis
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Development and validation of radiology-clinical statistical and machine learning model for stroke-associated pneumonia after first intracerebral haemorrhage.

BMC pulmonary medicine 39048959
BACKGROUND: Society is burdened with stroke-associated pneumonia (SAP) after intracerebral haemorrhage (ICH). Cerebral small vessel disease (CSVD) complicates clinical manifestations of stroke. In this study, we redefined the CSVD burden score and in...
Aged Aged, 80 and over Cerebral Hemorrhage Cerebral Small Vessel Diseases Female Humans Logistic Models Machine Learning Male Middle Aged Models, Statistical Pneumonia Retrospective Studies Risk Factors Stroke Tomography, X-Ray Computed
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Artificial intelligence/machine learning for neuroimaging to predict hemorrhagic transformation: Systematic review/meta-analysis.

Journal of neuroimaging : official journal of the American Society of Neuroimaging 39034604
BACKGROUND AND PURPOSE: Early and reliable prediction of hemorrhagic transformation (HT) in patients with acute ischemic stroke (AIS) is crucial for treatment decisions and early intervention. The purpose of this study was to conduct a systematic rev...
Artificial Intelligence Cerebral Hemorrhage Humans Ischemic Stroke Machine Learning Neuroimaging
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Prediction of hematoma expansion in spontaneous intracerebral hemorrhage using a multimodal neural network.

Scientific reports 39013990
Hematoma expansion occasionally occurs in patients with intracerebral hemorrhage (ICH), associating with poor outcome. Multimodal neural networks incorporating convolutional neural network (CNN) analysis of images and neural network analysis of tabul...
Aged Aged, 80 and over Cerebral Hemorrhage Female Hematoma Humans Machine Learning Male Middle Aged Neural Networks, Computer Retrospective Studies ROC Curve Tomography, X-Ray Computed
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Hybrid clinical-radiomics model based on fully automatic segmentation for predicting the early expansion of spontaneous intracerebral hemorrhage: A multi-center study.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association 39222703
BACKGROUND: Early prediction of hematoma expansion (HE) is important for the development of therapeutic strategies for spontaneous intracerebral hemorrhage (sICH). Radiomics can help to predict early hematoma expansion in intracerebral hemorrhage. Ho...
Aged Aged, 80 and over Automation Cerebral Hemorrhage China Decision Support Techniques Deep Learning Disease Progression Female Hematoma Humans Male Middle Aged Nomograms Predictive Value of Tests Prognosis Radiographic Image Interpretation, Computer-Assisted Radiomics Reproducibility of Results Retrospective Studies Risk Assessment Risk Factors Time Factors Tomography, X-Ray Computed
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Deep learning models for separate segmentations of intracerebral and intraventricular hemorrhage on head CT and segmentation quality assessment.

Medical physics 39133935
BACKGROUND: The volume measurement of intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) provides critical information for precise treatment of patients with spontaneous ICH but remains a big challenge, especially for IVH segmentati...
Cerebral Hemorrhage Deep Learning Head Humans Image Processing, Computer-Assisted Quality Control Tomography, X-Ray Computed
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Phenotypes of Patients with Intracerebral Hemorrhage, Complications, and Outcomes.

Neurocritical care 39107659
BACKGROUND: The objective of this study was to define clinically meaningful phenotypes of intracerebral hemorrhage (ICH) using machine learning.
Aged Cerebral Hemorrhage Female Glasgow Coma Scale Hematoma Humans Machine Learning Male Middle Aged Outcome Assessment, Health Care Phenotype Seizures
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A Deep Learning-Based Framework for Predicting Intracerebral Hematoma Expansion Using Head Non-contrast CT Scan.

Academic radiology 39107191
RATIONALE AND OBJECTIVES: Hematoma expansion (HE) in intracerebral hemorrhage (ICH) is a critical factor affecting patient outcomes, yet effective clinical tools for predicting HE are currently lacking. We aim to develop a fully automated framework b...
Aged Cerebral Hemorrhage Deep Learning Female Hematoma Humans Male Middle Aged Prospective Studies Retrospective Studies Sensitivity and Specificity Tomography, X-Ray Computed
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Enhancing Outcome Prediction in Intracerebral Hemorrhage Through Deep Learning: A Retrospective Multicenter Study.

Academic radiology 39095262
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).
Aged Cerebral Hemorrhage Deep Learning Female Glasgow Coma Scale Humans Male Middle Aged Predictive Value of Tests Prognosis Retrospective Studies Tomography, X-Ray Computed
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