PT  - JOURNAL ARTICLE
AU  - Pierre Orban
AU  - Christian Dansereau
AU  - Laurence Desbois
AU  - Violaine Mongeau-Pérusse
AU  - Charles-Édouard Giguère
AU  - Hien Nguyen
AU  - Adrianna Mendrek
AU  - Emmanuel Sti
AU  - Pierre Bellec
TI  - Multisite generalizability of schizophrenia diagnosis classification based on functional brain connectivity
AID  - 10.1101/141192
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 141192
4099  - http://biorxiv.org/content/early/2017/05/24/141192.short
4100  - http://biorxiv.org/content/early/2017/05/24/141192.full
AB  - 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.