Multisite generalizability of schizophrenia diagnosis classification based on functional brain connectivity Academic Article uri icon

abstract

  • Our objective was to assess the generalizability, across sites and cognitive contexts, of schizophrenia classification based on functional brain connectivity. We tested different training-test scenarios combining fMRI data from 191 schizophrenia patients and 191 matched healthy controls obtained at 6 scanning sites and under different task conditions. Diagnosis classification accuracy generalized well to a novel site and cognitive context provided data from multiple sites were used for classifier training. By contrast, lower classification accuracy was achieved when data from a single distinct site was used for training. These findings indicate that it is beneficial to use multisite data to train fMRI-based classifiers intended for large-scale use in the clinical realm.

authors

  • Orban, Pierre
  • Dansereau, Christian
  • Desbois, Laurence
  • Mongeau-Pérusse, Violaine
  • Giguère, Charles-Édouard
  • Nguyen, Hien
  • Mendrek, Adrianna
  • Stip, Emmanuel
  • Bellec, Pierre

publication date

  • 2018