Decoding post-stroke motor function from structural brain imaging

Decoding post-stroke motor function from structural brain imaging

Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine learning in structural imaging to investigate dise...

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Bibliographic Details
Main Authors: Jane M. Rondina, Maurizio Filippone, Mark Girolami, Nick S. Ward
Format: Article
Language:English
Published: Elsevier 2016-01-01
Series:NeuroImage: Clinical
Subjects:
Stroke
Motor impairment
Lesion patterns
Machine learning
Gaussian processes
Multiple kernel learning
Features extraction
Patterns of lesion probability
Lesion load
Online Access:http://www.sciencedirect.com/science/article/pii/S2213158216301346

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http://www.sciencedirect.com/science/article/pii/S2213158216301346

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