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ROCs of cross-validation accuracy predicting SZ from ASD patients in the training-naive test data set as a function of the number of diagnostic features used for prediction. Diagnostic features are the combination of the SZ and ASD features when trained against common control group. Best performance was achieved using the top 40–50 RFE features which resulted in 75% accuracy with 90% sensitivity (TPR) and 60% specificity (1 − FPR).
