M167. MACHINE LEARNING CLASSIFICATION OF FIRST-EPISODE PSYCHOSIS USING CORTICAL THICKNESS IN A LARGE MULTICENTER MRI STUDY

BACKGROUND: Machine learning classifications of first-episode psychosis (FEP) using neuroimaging have predominantly analyzed brain volumes. Some studies examined cortical thickness data, but most of them have used parcellation approaches with data from single sites, which limits claims of generaliza...

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Detalles Bibliográficos
Autores principales: Pigoni, Alessandro, Dwyer, Dominic, Squarcina, Letizia, Borgwardt, Stefan, Crespo-Facorro, Benedicto, Dazzan, Paola, Smesny, Stefan, Spaniel, Filip, Spalletta, Gianfranco, Sanfelici, Rachele, Antonucci, Linda A, Reuf, Anne, Oeztuerk, Oemer, Schmidt, André, Ciufolini, Simone, Harrisberger, Fabienne, Langbein, Kerstin, Reichenbach, Juergen, Zaytseva, Yulia, Bellani, Marcella, Ruggeri, Mirella, Lasalvia, Antonio, Tordesillas-Gutiérrez, Diana, Koutsouleris, Nikolaos, Brambilla, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Poster Session II
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7234338/
http://dx.doi.org/10.1093/schbul/sbaa030.479

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7234338/
http://dx.doi.org/10.1093/schbul/sbaa030.479

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