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SummaryCognitive impairment is a frequent and disabling sequela of stroke. There is however incomplete understanding of how lesion topographies in the left and right cerebral hemisphere brain interact to cause distinct cognitive deficits. We integrated machine learning and Bayesian hierarchical modeling to enable hemisphere-aware analysis of 1080 subacute ischemic stroke patients with deep profiling ∼3 months after stroke. We show relevance of the left hemisphere in the prediction of languagedoi:10.1101/2020.08.22.262873 fatcat:gb53zudf6rg4jfqu27nhn5te3a