Multisite generalizability of schizophrenia diagnosis classification based on functional brain connectivity

作者：Orban Pierre; Dansereau Christian; De**ois Laurence; Mongeau Perusse Violaine; Giguere Charles Edouard; Hien Nguyen; Mendrek Adrianna; Stip Emmanuel; Bellec Pierre

来源：Schizophrenia Research, 2018, 192: 167-171.

DOI：10.1016/j.schres.2017.05.027

• Schizophrenia
• fMRI
• Machine learning
• Classification
• Multisite
• Cognition

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 BARI-based classifiers intended for large-scale use in the clinical realm.

• 出版日期2018-2