Neuroimaging increasingly exploits machine learning techniques in an attempt to achieve clinically relevant single-subject predictions. We will discuss the rationale behind a computational approach to neuroimaging-based single-subject inference, focusing on its potential for characterising disease mechanisms in individual subjects and mapping these characterisations to clinical predictions.
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