AIMC Topic: Ischemic Stroke

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Deep Learning-Based Acute Ischemic Stroke Lesion Segmentation Method on Multimodal MR Images Using a Few Fully Labeled Subjects.

Computational and mathematical methods in medicine Jan 29, 2021
Acute ischemic stroke (AIS) has been a common threat to human health and may lead to severe outcomes without proper and prompt treatment. To precisely diagnose AIS, it is of paramount importance to quantitatively evaluate the AIS lesions. By adopting...
Humans Databases, Factual Brain Deep Learning Computational Biology Magnetic Resonance Imaging Multimodal Imaging Ischemic Stroke Image Interpretation, Computer-Assisted
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Na MRI in ischemic stroke: Acquisition time reduction using postprocessing with convolutional neural networks.

NMR in biomedicine Jan 21, 2021
Quantitative Na magnetic resonance imaging (MRI) provides tissue sodium concentration (TSC), which is connected to cell viability and vitality. Long acquisition times are one of the most challenging aspects for its clinical establishment. K-space un...
Sodium Signal-To-Noise Ratio Female Aged Aged, 80 and over Male Middle Aged Humans Image Processing, Computer-Assisted Neural Networks, Computer Magnetic Resonance Imaging Ischemic Stroke
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Prediction of Clinical Outcome in Patients with Large-Vessel Acute Ischemic Stroke: Performance of Machine Learning versus SPAN-100.

AJNR. American journal of neuroradiology Jan 7, 2021
BACKGROUND AND PURPOSE: Traditional statistical models and pretreatment scoring systems have been used to predict the outcome for acute ischemic stroke patients (AIS). Our aim was to select the most relevant features in terms of outcome prediction on...
Prognosis Retrospective Studies Female Aged Humans Machine Learning Models, Statistical Male Ischemic Stroke Middle Aged Thrombolytic Therapy Cohort Studies Endovascular Procedures Treatment Outcome
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Identifiable Patterns of Trait, State, and Experience in Chronic Stroke Recovery.

Neurorehabilitation and neural repair Dec 22, 2020
BACKGROUND: Considerable evidence indicates that the functional connectome of the healthy human brain is highly stable, analogous to a fingerprint.
Aphasia Language Therapy Humans Female Aged Outcome Assessment, Health Care Adult Magnetic Resonance Imaging Individuality Chronic Disease Male Connectome Ischemic Stroke Middle Aged Stroke Rehabilitation Support Vector Machine
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Predictors of Stroke Outcome Extracted from Multivariate Linear Discriminant Analysis or Neural Network Analysis.

Journal of atherosclerosis and thrombosis Dec 9, 2020
AIM: The prediction of functional outcome is essential in the management of acute ischemic stroke patients. We aimed to explore the various prognostic factors with multivariate linear discriminant analysis or neural network analysis and evaluate the ...
Middle Aged Regression Analysis Recovery of Function Predictive Value of Tests Risk Factors Aged Aged, 80 and over Male Multivariate Analysis Ischemic Stroke Discriminant Analysis Alkaline Phosphatase Nutritional Status Humans Neural Networks, Computer Machine Learning Prognosis Retrospective Studies Female
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Artificial neural network based prediction of postthrombolysis intracerebral hemorrhage and death.

Scientific reports Nov 25, 2020
Despite the salient benefits of the intravenous tissue plasminogen activator (tPA), symptomatic intracerebral hemorrhage (sICH) remains a frequent complication and constitutes a major concern when treating acute ischemic stroke (AIS). This study expl...
Humans Neural Networks, Computer Phenotype Tissue Plasminogen Activator Female Treatment Outcome Aged Cerebral Hemorrhage Male Ischemic Stroke Cohort Studies Thrombolytic Therapy ROC Curve
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Electroencephalography Might Improve Diagnosis of Acute Stroke and Large Vessel Occlusion.

Stroke Sep 18, 2020
BACKGROUND AND PURPOSE: Clinical methods have incomplete diagnostic value for early diagnosis of acute stroke and large vessel occlusion (LVO). Electroencephalography is rapidly sensitive to brain ischemia. This study examined the diagnostic utility ...
Ischemic Attack, Transient Neural Networks, Computer Humans Female Logistic Models Sensitivity and Specificity Hemorrhagic Stroke Aged Male Ischemic Stroke Aged, 80 and over Middle Aged Electroencephalography Deep Learning Stroke
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The Probability of Ischaemic Stroke Prediction with a Multi-Neural-Network Model.

Sensors (Basel, Switzerland) Sep 3, 2020
As is known, cerebral stroke has become one of the main diseases endangering people's health; ischaemic strokes accounts for approximately 85% of cerebral strokes. According to research, early prediction and prevention can effectively reduce the inci...
Humans Neural Networks, Computer Middle Aged Ischemic Stroke Probability Female Brain Ischemia Aged Aged, 80 and over Male
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Exploring gene-gene interaction in family-based data with an unsupervised machine learning method: EPISFA.

Genetic epidemiology Sep 1, 2020
Gene-gene interaction (G × G) is thought to fill the gap between the estimated heritability of complex diseases and the limited genetic proportion explained by identified single-nucleotide polymorphisms. The current tools for exploring G × G were oft...
Family Epistasis, Genetic Linkage Disequilibrium Multifactor Dimensionality Reduction Models, Genetic Unsupervised Machine Learning Ischemic Stroke Factor Analysis, Statistical Humans Algorithms Case-Control Studies
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Automatic detection of acute ischemic stroke using non-contrast computed tomography and two-stage deep learning model.

Computer methods and programs in biomedicine Aug 15, 2020
BACKGROUND AND OBJECTIVE: Currently, it is challenging to detect acute ischemic stroke (AIS)-related changes on computed tomography (CT) images. Therefore, we aimed to develop and evaluate an automatic AIS detection system involving a two-stage deep ...
Humans Ischemic Stroke Tomography, X-Ray Computed Stroke Deep Learning Brain Ischemia
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