Predicting outcome and recovery after stroke with lesions extracted from MRI images
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Computational neurorehabilitation: modeling plasticity and learning to predict recoveryThe PLORAS Database: A data repository for Predicting Language Outcome and Recovery After StrokeIndividualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjectsAutomated segmentation of chronic stroke lesions using LINDA: Lesion identification with neighborhood data analysis.Antigliadin Antibodies (AGA IgG) Are Related to Neurochemistry in Schizophrenia.Multivariate lesion-symptom mapping using support vector regression.Stroke Recovery: Surprising Influences and Residual Consequences.Exploring the brain's structural connectome: A quantitative stroke lesion-dysfunction mapping studyLesion Location-Based Prediction of Visual Field Improvement after Cerebral Infarction.Characterising the grey matter correlates of leukoaraiosis in cerebral small vessel disease.Specifying the role of the left prefrontal cortex in word selection.The association of insular stroke with lesion volumeStructural connectome disruption at baseline predicts 6-months post-stroke outcomeDecoding post-stroke motor function from structural brain imagingComparing language outcomes in monolingual and bilingual stroke patients.A Lesion-Proof Brain? Multidimensional Sensorimotor, Cognitive, and Socio-Affective Preservation Despite Extensive Damage in a Stroke Patient.Cortical reorganization after stroke: how much and how functional?Right hemisphere structural adaptation and changing language skills years after left hemisphere stroke.Neural substrates of lower extremity motor, balance, and gait function after supratentorial stroke using voxel-based lesion symptom mapping.Update in Aphasia Research.Biomarkers of stroke recovery: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable.Brain regions important for recovery after severe post-stroke upper limb paresisTen problems and solutions when predicting individual outcome from lesion site after stroke.Important considerations in lesion-symptom mapping: Illustrations from studies of word comprehension.Coherent neural oscillations predict future motor and language improvement after stroke.Converging evidence for a cortico-subcortical network mediating lexical retrieval.Triangulation of language-cognitive impairments, naming errors and their neural bases post-stroke.Enhanced estimations of post-stroke aphasia severity using stacked multimodal predictions.Using multi-level Bayesian lesion-symptom mapping to probe the body-part-specificity of gesture imitation skills.Agreed Definitions and a Shared Vision for New Standards in Stroke Recovery Research: The Stroke Recovery and Rehabilitation Roundtable Taskforce.Neuropsychology and cognitive neuroscience in the fMRI era: A recapitulation of localizationist and connectionist views.Etiology of language network changes during recovery of aphasia after stroke.Contemporary Approaches to the Management of Post-stroke Apraxia of Speech.Predicting Recovery in Acute Post-stroke Aphasia.How distributed processing produces false negatives in voxel-based lesion-deficit analyses.Artificial intelligence in healthcare: past, present and future.Biomarkers of Stroke Recovery: Consensus-Based Core Recommendations from the Stroke Recovery and Rehabilitation Roundtable.Agreed definitions and a shared vision for new standards in stroke recovery research: The Stroke Recovery and Rehabilitation Roundtable taskforce.Structural neuroimaging as clinical predictor: A review of machine learning applicationsInsights into early language recovery: from basic principles to practical applications
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Predicting outcome and recovery after stroke with lesions extracted from MRI images
description
article científic
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article scientifique
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articolo scientifico
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artigo científico
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bilimsel makale
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scientific article published on 22 March 2013
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vedecký článok
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vetenskaplig artikel
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videnskabelig artikel
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vědecký článek
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name
Predicting outcome and recovery after stroke with lesions extracted from MRI images
@en
Predicting outcome and recovery after stroke with lesions extracted from MRI images.
@nl
type
label
Predicting outcome and recovery after stroke with lesions extracted from MRI images
@en
Predicting outcome and recovery after stroke with lesions extracted from MRI images.
@nl
prefLabel
Predicting outcome and recovery after stroke with lesions extracted from MRI images
@en
Predicting outcome and recovery after stroke with lesions extracted from MRI images.
@nl
P2860
P50
P1433
P1476
Predicting outcome and recovery after stroke with lesions extracted from MRI images
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P2093
Thomas M H Hope
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P304
P356
10.1016/J.NICL.2013.03.005
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2013-03-22T00:00:00Z