OCD patients from healthy controls using structural neuroimaging data at the individual subject level. We investigated machine learning classification performance in both single-site and multi-site samples using different validation strategies to assess generalizability. Furthermore, the large sample size enables investigation of the influence of clinical heterogeneity by stratification and subsampling, in order to assess the influence of clinical variability on classification accuracy.
