Use of Neuroanatomical Pattern Classification to Identify Subjects in At-Risk Mental States of Psychosis and Predict Disease Transition

CONTEXT: Identification of individuals at high risk of developing psychosis has relied on prodromal symptomatology. Recently, machine learning algorithms have been successfully used for magnetic resonance imaging–based diagnostic classification of neuropsychiatric patient populations. OBJECTIVE: To...

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Main Authors: Koutsouleris, Nikolaos, Meisenzahl, Eva M., Davatzikos, Christos, Bottlender, Ronald, Frodl, Thomas, Scheuerecker, Johanna, Schmitt, Gisela, Zetzsche, Thomas, Decker, Petra, Reiser, Maximilian, Möller, Hans-Jürgen, Gaser, Christian
Format: Artigo
Sprog:Inglês
Udgivet: 2009
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Article
Online adgang:https://ncbi.nlm.nih.gov/pmc/articles/PMC4135464/
https://ncbi.nlm.nih.gov/pubmed/19581561
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1001/archgenpsychiatry.2009.62
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