AIMC Topic: Cerebral Hemorrhage

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Hematoma expansion prediction in intracerebral hemorrhage patients by using synthesized CT images in an end-to-end deep learning framework.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 5, 2024
Spontaneous intracerebral hemorrhage (ICH) is a type of stroke less prevalent than ischemic stroke but associated with high mortality rates. Hematoma expansion (HE) is an increase in the bleeding that affects 30%-38% of hemorrhagic stroke patients. I...
Deep Learning Cerebral Hemorrhage Radiographic Image Interpretation, Computer-Assisted Hematoma Humans Tomography, X-Ray Computed Male
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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 Aug 31, 2024
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...
Hematoma Automation Risk Factors Deep Learning Aged Male Humans China Nomograms Retrospective Studies Aged, 80 and over Decision Support Techniques Time Factors Middle Aged Cerebral Hemorrhage Tomography, X-Ray Computed Radiomics Prognosis Risk Assessment Female Predictive Value of Tests Disease Progression Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted
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Identification of immune-related biomarkers for intracerebral hemorrhage diagnosis based on RNA sequencing and machine learning.

Frontiers in immunology Aug 30, 2024
BACKGROUND: Intracerebral hemorrhage (ICH) is a severe stroke subtype with high morbidity, disability, and mortality rates. Currently, no biomarkers for ICH are available for use in clinical practice. We aimed to explore the roles of RNAs in ICH path...
RNA, Long Noncoding Male Cerebral Hemorrhage Transcriptome Middle Aged Humans Gene Expression Profiling Case-Control Studies Biomarkers Machine Learning RNA, Messenger Female Macrophages Sequence Analysis, RNA Aged Animals
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Deep learning models for separate segmentations of intracerebral and intraventricular hemorrhage on head CT and segmentation quality assessment.

Medical physics Aug 12, 2024
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...
Quality Control Head Humans Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Cerebral Hemorrhage
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Phenotypes of Patients with Intracerebral Hemorrhage, Complications, and Outcomes.

Neurocritical care Aug 6, 2024
BACKGROUND: The objective of this study was to define clinically meaningful phenotypes of intracerebral hemorrhage (ICH) using machine learning.
Machine Learning Phenotype Female Aged Humans Outcome Assessment, Health Care Hematoma Glasgow Coma Scale Male Middle Aged Cerebral Hemorrhage Seizures
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A Deep Learning-Based Framework for Predicting Intracerebral Hematoma Expansion Using Head Non-contrast CT Scan.

Academic radiology Aug 5, 2024
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...
Humans Middle Aged Deep Learning Female Cerebral Hemorrhage Aged Hematoma Sensitivity and Specificity Male Prospective Studies Retrospective Studies Tomography, X-Ray Computed
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Enhancing Outcome Prediction in Intracerebral Hemorrhage Through Deep Learning: A Retrospective Multicenter Study.

Academic radiology Aug 1, 2024
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).
Middle Aged Deep Learning Cerebral Hemorrhage Predictive Value of Tests Female Aged Male Glasgow Coma Scale Humans Prognosis Retrospective Studies Tomography, X-Ray Computed
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Advancements in prognostic markers and predictive models for intracerebral hemorrhage: from serum biomarkers to artificial intelligence models.

Neurosurgical review Jul 31, 2024
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 Machine Learning Biomarkers Prognosis Cerebral Hemorrhage Humans
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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 Jul 24, 2024
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...
Stroke Cerebral Small Vessel Diseases Logistic Models Tomography, X-Ray Computed Aged, 80 and over Models, Statistical Female Humans Cerebral Hemorrhage Male Risk Factors Machine Learning Pneumonia Middle Aged Aged Retrospective Studies
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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 Jul 21, 2024
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...
Humans Artificial Intelligence Machine Learning Cerebral Hemorrhage Ischemic Stroke Neuroimaging
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