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While medical imaging typically provides massive amounts of data, the automatic extraction of relevant information in a given applicative context remains a difficult challenge in general. With functional MRI (fMRI), the data provide an indirect measurement of brain activity, that can be related to behavioral information. It is now standard to formulate this relation as a machine learning problem where...
Multivariate pattern classification is emerging as a powerful tool for analysis of fMRI group studies and has the advantage that it utilizes spatial correlation between brain voxels. However, this makes quantifying the information content of brain voxels and localizing informative brain regions difficult. In this paper we a probabilistic Gaussian process classifiers to compute a sensitive measure...
There has been a growing interest in applying pattern classification methods to discriminate patients with neurodegenerative diseases from normal controls using structural MRI data. Despite an impressive array of publications, most applications are framed as discrimination problems with categorical class decisions. For many clinical applications, probabilistic estimation would be more useful, especially...
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