| scholarly article | Q13442814 |
| P50 | author | Mohamed L. Seghier | Q41769619 |
| Alexander P. Leff | Q41790228 | ||
| Catherine J. Price | Q69389594 | ||
| P2093 | author name string | Thomas M H Hope | |
| P2860 | cites work | Acute stroke: prognosis and a prediction of the effect of medical treatment on outcome and health care utilization. The Copenhagen Stroke Study | Q40875137 |
| Lesion identification using unified segmentation-normalisation models and fuzzy clustering | Q41790182 | ||
| Early functional magnetic resonance imaging activations predict language outcome after stroke. | Q45963044 | ||
| Cerebellar involvement in verb generation: an fMRI study | Q48395247 | ||
| Predicting outcome after acute and subacute stroke: development and validation of new prognostic models | Q48638450 | ||
| A longitudinal study of speech fluency in aphasia: CT correlates of recovery and persistent nonfluency | Q48741293 | ||
| The profile of recovery from stroke and factors influencing outcome. | Q51229357 | ||
| Generative and recognition models for neuroanatomy. | Q51991189 | ||
| Optimisation of the 3D MDEFT sequence for anatomical brain imaging: technical implications at 1.5 and 3 T. | Q52003093 | ||
| The role of the human thalamus in language and memory: evidence from electrophysiological studies. | Q52027971 | ||
| How Long Is the Recovery of Global Aphasia? Twenty-Five Years of Follow-up in a Patient With Left Hemisphere Stroke | Q56032177 | ||
| Aphasia in acute stroke and relation to outcome | Q56038500 | ||
| A New Method for Predicting Recovery After Stroke | Q57588230 | ||
| Computer-assisted clinical decision-making | Q69233514 | ||
| Aphasia in acute stroke: incidence, determinants, and recovery | Q71778461 | ||
| Disablement and quality of life after stroke | Q72823964 | ||
| Impaired speech repetition and left parietal lobe damage | Q24613895 | ||
| A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data | Q26722188 | ||
| Models of the aging brain structure and individual decline | Q27313508 | ||
| Unified segmentation | Q29616050 | ||
| The anatomy underlying acute versus chronic spatial neglect: a longitudinal study | Q30469910 | ||
| Two tongues, one brain: imaging bilingual speech production | Q30474607 | ||
| Impairment of speech production predicted by lesion load of the left arcuate fasciculus | Q30503963 | ||
| Biomarker discovery in microarray gene expression data with Gaussian processes | Q30991432 | ||
| Language rehabilitation in chronic aphasia and time postonset: a review of single-subject data | Q31075810 | ||
| Predicting long-term outcome after acute ischemic stroke: a simple index works in patients from controlled clinical trials | Q33327657 | ||
| The role of the arcuate fasciculus in conduction aphasia | Q33494788 | ||
| Predicting language outcome and recovery after stroke: the PLORAS system | Q33538484 | ||
| Recovery after stroke | Q33618350 | ||
| Predicting the outcome of acute stroke: a prognostic score | Q33619749 | ||
| Recovery from aphasia and neglect. | Q33726560 | ||
| Predicting clinical scores from magnetic resonance scans in Alzheimer's disease | Q33857210 | ||
| Recovery from post-stroke aphasia: lessons from brain imaging and implications for rehabilitation and biological treatments. | Q34059517 | ||
| Aphasia after stroke: type, severity and prognosis. The Copenhagen aphasia study | Q34268105 | ||
| Positron emission tomographic studies of the processing of single words | Q34365871 | ||
| Paul Broca's historic cases: high resolution MR imaging of the brains of Leborgne and Lelong | Q34615252 | ||
| The prognosis for aphasia in stroke | Q35053549 | ||
| The relationship between executive dysfunction and post-stroke mortality: a population-based cohort study | Q35963049 | ||
| Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification | Q37299456 | ||
| Variability in recovery from aphasia | Q37310535 | ||
| Post-stroke aphasia prognosis: a review of patient-related and stroke-related factors | Q37852123 | ||
| Early prediction of outcome of activities of daily living after stroke: a systematic review | Q37862915 | ||
| Semantic context and visual feature effects in object naming: an fMRI study using arterial spin labeling | Q38386831 | ||
| Task-dependent modulations of prefrontal and hippocampal activity during intrinsic word production | Q38389305 | ||
| An fMRI investigation of syllable sequence production. | Q38406650 | ||
| Lesion sites that predict the ability to gesture how an object is used | Q39803089 | ||
| P921 | main subject | magnetic resonance imaging | Q161238 |
| P304 | page(s) | 424-433 | |
| P577 | publication date | 2013-03-22 | |
| P1433 | published in | NeuroImage: Clinical | Q22907265 |
| P1476 | title | Predicting outcome and recovery after stroke with lesions extracted from MRI images | |
| P478 | volume | 2 |
| Q92649432 | A Comparison of Shallow and Deep Learning Methods for Predicting Cognitive Performance of Stroke Patients From MRI Lesion Images |
| Q37574761 | A Lesion-Proof Brain? Multidimensional Sensorimotor, Cognitive, and Socio-Affective Preservation Despite Extensive Damage in a Stroke Patient |
| Q93154541 | A lesion and connectivity-based hierarchical model of chronic aphasia recovery dissociates patients and healthy controls |
| Q45963344 | Agreed Definitions and a Shared Vision for New Standards in Stroke Recovery Research: The Stroke Recovery and Rehabilitation Roundtable Taskforce. |
| Q52089447 | Agreed definitions and a shared vision for new standards in stroke recovery research: The Stroke Recovery and Rehabilitation Roundtable taskforce. |
| Q33809544 | Antigliadin Antibodies (AGA IgG) Are Related to Neurochemistry in Schizophrenia |
| Q50420737 | Artificial intelligence in healthcare: past, present and future |
| Q90025698 | Assessing and mapping language, attention and executive multidimensional deficits in stroke aphasia |
| Q30277771 | Automated segmentation of chronic stroke lesions using LINDA: Lesion identification with neighborhood data analysis |
| Q51778008 | Biomarkers of Stroke Recovery: Consensus-Based Core Recommendations from the Stroke Recovery and Rehabilitation Roundtable. |
| Q38659060 | Biomarkers of stroke recovery: Consensus-based core recommendations from the Stroke Recovery and Rehabilitation Roundtable. |
| Q92577287 | Brain age prediction in stroke patients: Highly reliable but limited sensitivity to cognitive performance and response to cognitive training |
| Q38667791 | Brain regions important for recovery after severe post-stroke upper limb paresis |
| Q36042708 | Characterising the grey matter correlates of leukoaraiosis in cerebral small vessel disease. |
| Q98177258 | Clinical and neuroimaging factors associated with aphasia severity in stroke patients: diffusion tensor imaging study |
| Q38985951 | Coherent neural oscillations predict future motor and language improvement after stroke |
| Q37238097 | Comparing language outcomes in monolingual and bilingual stroke patients. |
| Q26748823 | Computational neurorehabilitation: modeling plasticity and learning to predict recovery |
| Q49853114 | Contemporary Approaches to the Management of Post-stroke Apraxia of Speech |
| Q39413452 | Converging evidence for a cortico-subcortical network mediating lexical retrieval |
| Q38115085 | Cortical reorganization after stroke: how much and how functional? |
| Q37199212 | Decoding post-stroke motor function from structural brain imaging |
| Q88664322 | Differences in swallow physiology in patients with left and right hemispheric strokes |
| Q45946379 | Enhanced estimations of post-stroke aphasia severity using stacked multimodal predictions. |
| Q57493111 | Estimating the statistical significance of spatial maps for multivariate lesion-symptom analysis |
| Q47655364 | Etiology of language network changes during recovery of aphasia after stroke |
| Q35554155 | Exploring the brain's structural connectome: A quantitative stroke lesion-dysfunction mapping study |
| Q89480877 | Fighting healthcare rocketing costs with value-based medicine: the case of stroke management |
| Q50300943 | How distributed processing produces false negatives in voxel-based lesion-deficit analyses. |
| Q38895013 | Important considerations in lesion-symptom mapping: Illustrations from studies of word comprehension. |
| Q28656446 | Individualized Gaussian process-based prediction and detection of local and global gray matter abnormalities in elderly subjects |
| Q58249345 | Insights into early language recovery: from basic principles to practical applications |
| Q92095574 | Investigating the effect of changing parameters when building prediction models for post-stroke aphasia |
| Q91646826 | Left frontotemporal effective connectivity during semantic feature judgments in patients with chronic aphasia and age-matched healthy controls |
| Q35852594 | Lesion Location-Based Prediction of Visual Field Improvement after Cerebral Infarction |
| Q89449631 | Leukoaraiosis is independently associated with naming outcome in poststroke aphasia |
| Q90475272 | Machine Learning Methods Predict Individual Upper-Limb Motor Impairment Following Therapy in Chronic Stroke |
| Q104617711 | Machine learning-based multimodal prediction of language outcomes in chronic aphasia |
| Q61811935 | Mapping acute lesion locations to physiological swallow impairments after stroke |
| Q34422382 | Multivariate lesion-symptom mapping using support vector regression |
| Q38416374 | Neural substrates of lower extremity motor, balance, and gait function after supratentorial stroke using voxel-based lesion symptom mapping |
| Q64084775 | Neuroplasticity of Language Networks in Aphasia: Advances, Updates, and Future Challenges |
| Q47617124 | Neuropsychology and cognitive neuroscience in the fMRI era: A recapitulation of localizationist and connectionist views |
| Q90176415 | Predicting Early Post-stroke Aphasia Outcome From Initial Aphasia Severity |
| Q49937075 | Predicting Recovery in Acute Post-stroke Aphasia |
| Q90406339 | Predicting language outcomes after stroke: Is structural disconnection a useful predictor? |
| Q96610140 | Predicting post-stroke aphasia from brain imaging |
| Q90431938 | Predicting the pattern and severity of chronic post-stroke language deficits from functionally-partitioned structural lesions |
| Q92929718 | Progression of Aphasia Severity in the Chronic Stages of Stroke |
| Q58121111 | Relative contributions of lesion location and lesion size to predictions of varied language deficits in post-stroke aphasia |
| Q90265063 | Rich-Club Organization: An Important Determinant of Functional Outcome After Acute Ischemic Stroke |
| Q38377514 | Right hemisphere structural adaptation and changing language skills years after left hemisphere stroke. |
| Q36461951 | Specifying the role of the left prefrontal cortex in word selection. |
| Q35249075 | Stroke Recovery: Surprising Influences and Residual Consequences |
| Q36999211 | Structural connectome disruption at baseline predicts 6-months post-stroke outcome |
| Q57040013 | Structural neuroimaging as clinical predictor: A review of machine learning applications |
| Q38833341 | Ten problems and solutions when predicting individual outcome from lesion site after stroke |
| Q92275516 | The Neurologist and Artificial Intelligence: Titans at Crossroads |
| Q28607093 | The PLORAS Database: A data repository for Predicting Language Outcome and Recovery After Stroke |
| Q36518181 | The association of insular stroke with lesion volume |
| Q63952184 | Transcranial Direct Current Stimulation as a Novel Method for Enhancing Aphasia Treatment Effects |
| Q44952679 | Triangulation of language-cognitive impairments, naming errors and their neural bases post-stroke. |
| Q38528301 | Update in Aphasia Research |
| Q45946468 | Using multi-level Bayesian lesion-symptom mapping to probe the body-part-specificity of gesture imitation skills. |
| Q102371642 | White matter hyperintensities at critical crossroads for executive function and verbal abilities in small vessel disease |
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