Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach

Paris Alexandros Lalousis,Joseph Kambeitz,Theresa Haidl,Alessandro Bertolino,Adele Ferro,Carolina Bonivento,Marlene Rosen,Rachel Upthegrove,Nikolaos Koutsouleris,Rebekka Lencer,Katharine Chisholm,Christos Pantelis,Paolo Brambilla,Stefan Borgwardt,Lianne Schmaal,Stephan Ruhrmann,Dominic Dwyer ,Siân Lowri Griffiths ,Stephen Wood ,André Schmidt ,Raimo K R Salokangas ,Renate Reniers ,Frauke Schultze‐Lutter ,Eva Meisenzahl

doi:10.1016/j.biopsych.2021.02.598

Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach

Paris Alexandros Lalousis, Joseph Kambeitz + Show 22 more

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https://doi.org/10.1016/j.biopsych.2021.02.598

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Journal: Biological Psychiatry

Publication Date: Apr 27, 2021

Affiliation: University Hospital Cologne, University of Cologne, Gold Skin Care Center, Polytechnic University of Bari, University of Bari Aldo Moro, University of Birmingham, Orygen Youth Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, IRCCS Eugenio Medea, University of Münster, Aston University, University of Basel, University of Turku, Heinrich Heine University Düsseldorf

#Diagnostic Heterogeneity #Recent Onset Depression + Show 8 more

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Abstract

Diagnostic heterogeneity within and across psychotic and affective disorders challenges accurate treatment selection, particularly in 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.

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