Subtyping schizophrenia based on symptomatology and cognition using a data driven approach
Luis FS Castro-de-Araujo, Daiane B Machado, Mauricio L Barreto, Richard AA Kanaan
Psychiatry Research: Neuroimaging | ELSEVIER IRELAND LTD | Published : 2020
Schizophrenia is a highly heterogeneous disorder, not only in its phenomenology but in its clinical course. This limits the usefulness of the diagnosis as a basis for both research and clinical management. Methods of reducing this heterogeneity may inform the diagnostic classification. With this in mind, we performed k-means clustering with symptom and cognitive measures to generate groups in a machine-driven way. We found that our data was best organised in three clusters: high cognitive performance, high positive symptomatology, low positive symptomatology. We hypothesized that these clusters represented biological categories, which we tested by comparing these groups in terms of brain vol..View full abstract
LFCA and DBM are funded by The Wellcome Trust via a research associate scholarship at Center of Data and Knowledge Integration for Health (CIDACS), Fundacao Oswaldo Cruz (Fiocruz).