Classification for medicated patients vs. HC using neuroimaging data only resulted in AUC of 0.66 (95% CI = 0.60–0.73; pcorrected < 0.001) and AUC of 0.70 (95% CI = 0.64–0.76; pcorrected < 0.001) for SVM-RBF. Using covariates only resulted in AUC of 0.71 (95% CI = 0.65–0.77; pcorrected < 0.001), and neuroimaging data following correction for covariates resulted in AUC of 0.59 (95% CI = 0.52–0.66; pcorrected = 0.053), and higher AUC of 0.62 (95% CI = 0.55–0.69; pcorrected = 0.007) for XGB. Next, classification of unmedicated patients vs. HC using neuroimaging data only resulted in an AUC of 0.58 (95% CI = 0.51–0.68; pcorrected = 0.12) with significant classifier performance for PCA + SVM-RBF with AUC of 0.61 (95% CI = 0.55–0.68; pcorrected = 0.007). Using covariates only resulted in AUC of 0.64 (95% CI = 0.58–0.73; pcorrected < 0.001), and using neuroimaging data following correction for covariates resulted in AUC of 0.52 (95% CI = 0.45–0.59; pcorrected = 1). Finally, classification of medicated vs. unmedicated patients using neuroimaging data only resulted in AUC of 0.74 (95% CI =
