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Hematoma

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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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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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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 39260113
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...
Cerebral Hemorrhage Deep Learning Hematoma Humans Male Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed
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Development of machine learning prediction model for AKI after craniotomy and evacuation of hematoma in craniocerebral trauma.

Medicine 39496042
The aim of this study was to develop a machine-learning prediction model for AKI after craniotomy and evacuation of hematoma in craniocerebral trauma. We included patients who underwent craniotomy and evacuation of hematoma due to traumatic brain inj...
Acute Kidney Injury Adult Aged Craniocerebral Trauma Craniotomy Female Hematoma Humans Machine Learning Male Middle Aged Postoperative Complications Retrospective Studies ROC Curve
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Prediction of prognosis in patients with cerebral contusions based on machine learning.

Scientific reports 39738368
Traumatic brain injury (TBI) is a global issue and a major cause of patient mortality, and cerebral contusions (CCs) is a common primary TBI. The haemorrhagic progression of a contusion (HPC) poses a significant risk to patients' lives, and effective...
Adolescent Adult Aged Algorithms Brain Contusion Decision Trees Female Hematoma Humans Machine Learning Male Middle Aged Prognosis ROC Curve Young Adult
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Evaluation of Pregnancy Risks in Women with Subchorionic Hematoma Using Machine Learning Models.

Medical science monitor : international medical journal of experimental and clinical research 39707645
BACKGROUND Subchorionic hematoma (SCH) can lead to blood accumulation and potentially affect pregnancy outcomes. Despite being a relatively common finding in early pregnancy, the effects of SCH on pregnancy outcomes such as miscarriage, stillbirth, a...
Abortion, Spontaneous Adult Birth Weight Chorion Female Gestational Age Hematoma Humans Infant, Newborn Logistic Models Machine Learning Pregnancy Pregnancy Complications Pregnancy Outcome Premature Birth Risk Factors Stillbirth
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Using artificial intelligence-based software for an unbiased discrimination of immune cell subtypes in the fracture hematoma and bone marrow of non-osteoporotic and osteoporotic mice.

PloS one 40299871
It is well established that the early inflammatory response following fracture is essential for initiating subsequent bone regeneration. An imbalance in inflammation, whether within the innate or adaptive immune response, can result in impaired fract...
Animals Artificial Intelligence Bone Marrow Female Flow Cytometry Fractures, Bone Granulocytes Hematoma Macrophages Mice Mice, Inbred C57BL Osteoporosis Software T-Lymphocytes
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Utilizing Machine Learning Techniques to Predict Negative Remodeling in Uncomplicated Type B Intramural Hematoma.

Annals of vascular surgery 40054615
BACKGROUND: To evaluate the effectiveness of machine learning (ML) techniques in predicting negative remodeling in uncomplicated Stanford type B intramural hematoma (IMHB) during the acute phase.
Aged Aortic Diseases Female Hematoma Humans Machine Learning Male Middle Aged Predictive Value of Tests Retrospective Studies Risk Assessment Risk Factors Vascular Remodeling
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