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bioRxiv · 10.1101/141192

Multisite Generalizability Of Schizophrenia Diagnosis Classification Based On Functional Brain Connectivity

Orban, P.·Dansereau, C.·Desbois, L.·Mongeau-Perusse, V.·Giguere, C.-E.·Nguyen, H.·Mendrek, A.·Stip, E.·Bellec, P.
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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.

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Orban, P., Dansereau, C., Desbois, L., Mongeau-Perusse, V., Giguere, C.-E., Nguyen, H., Mendrek, A., Stip, E., Bellec, P.. 2017-05-23. Multisite Generalizability Of Schizophrenia Diagnosis Classification Based On Functional Brain Connectivity. https://doi.org/10.1101/141192

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