An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine

@inproceedings{PetterssonYeo2014AnEC,
  title={An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine},
  author={William Pettersson-Yeo and Stefania Benetti and Andre F. Marquand and Richard Joules and Marco Catani and Stephen C. R. Williams and Paul Allen and Philip Mcguire and Andrea Mechelli},
  booktitle={Front. Neurosci.},
  year={2014}
}
In the pursuit of clinical utility, neuroimaging researchers of psychiatric and neurological illness are increasingly using analyses, such as support vector machine, that allow inference at the single-subject level. Recent studies employing single-modality data, however, suggest that classification accuracies must be improved for such utility to be realized. One possible solution is to integrate different data types to provide a single combined output classification; either by generating a… CONTINUE READING
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An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine

W Citation Pettersson-Yeo, S Benetti, +6 authors A Mechelli
Front. Neurosci. 8:189 • 2014

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Pettersson-Yeo, Benetti, +6 authors Mechelli
2014