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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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| Autors principals: | , , , , , , , , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2009
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| Matèries: | |
| Accés en línia: | 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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