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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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| Główni autorzy: | , , , , , , , , , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
2009
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| Hasła przedmiotowe: | |
| Dostęp online: | 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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