Stroke recovery therapeutics include many classes of intervention and numerous treatment
targets. Stroke is a very heterogeneous disease. As such, stroke recovery therapeutics …

Purpose: This paper reviews several studies whose aim was to understand the nature of
language recovery in chronic aphasia and identify predictors of how people may recover …

Post-stroke aphasia recovery, especially in the chronic phase, is challenging to predict.
Functional integrity of the brain and brain network topology have been suggested as …

The fusion of electroencephalography (EEG) with machine learning is transforming
rehabilitation. Our study introduces a neural network model proficient in distinguishing pre …

Neuroimaging data typically include multiple modalities, such as structural or functional
magnetic resonance imaging, diffusion tensor imaging, and positron emission tomography …

Defining reliable tools for early prediction of outcome is the main target for physicians to
guide care decisions in patients with brain injury. The application of machine learning (ML) …

Magnetic resonance imaging (MRI) and MRI based computational modelling studies provide
insights into severity and recovery of ischemic stroke patients. The presence of brain lesions …

Stroke is one of the leading causes of long-term disabilities in motor and cognition
functionality. An early and accurate prediction of rehabilitation outcomes can lead to a tailor …

This paper explores feature selection and fusion methods for predicting the clinical outcome
of post-stroke aphasia from medical imaging data. Utilizing a multimodal neuroimaging …

Purpose: Speech fluency has important diagnostic implications for individuals with
poststroke aphasia (PSA) as well as primary progressive aphasia (PPA), and quantitative …