A connectome-based approach to assess motor outcome after neonatal arterial ischemic stroke.

Mariam Al HarrachPablo PretzelSamuel GroeschelFrançois RousseauThijs DhollanderLucie Hertz-PannierJulien LefevreStéphane ChabrierMickael Dinomaisnull null

Published in: Annals of clinical and translational neurology (2021)

Using the connectivity measures of these links, the BBT score can be estimated using a multiple linear regression model. In addition, the presence or not of CP can also be predicted using the KNN classification algorithm. According to our results, the structural connectome can be an asset in the estimation of gross manual dexterity and can help uncover structural changes between brain regions related to NAIS.

Keyphrases

resting state
functional connectivity
machine learning
deep learning
atrial fibrillation
neural network
children with cerebral palsy
multiple sclerosis
brain injury