Journal article
Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach
PA Lalousis, SJ Wood, L Schmaal, K Chisholm, SL Griffiths, RLEP Reniers, A Bertolino, S Borgwardt, P Brambilla, J Kambeitz, R Lencer, C Pantelis, S Ruhrmann, RKR Salokangas, F Schultze-Lutter, C Bonivento, D Dwyer, A Ferro, T Haidl, M Rosen Show all
Schizophrenia Bulletin | OXFORD UNIV PRESS | Published : 2021
Abstract
Diagnostic heterogeneity within and across psychotic and affective disorders challenges accurate treatment selection, particularly in the early stages. Delineation of shared and distinct illness features at the phenotypic and brain levels may inform the development of more precise differential diagnostic tools. We aimed to identify prototypes of depression and psychosis to investigate their heterogeneity, with common, comorbid transdiagnostic symptoms. Analyzing clinical/neurocognitive and grey matter volume (GMV) data from the PRONIA database, we generated prototypic models of recent-onset depression (ROD) vs. recent-onset psychosis (ROP) by training support-vector machines to separate pati..
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Awarded by European Commission
Funding Acknowledgements
PRONIA is a Collaboration Project funded by the European Union under the 7th Framework Programme under grant agreement number 602152.