Fig. 1: Receiver operating characteristics (ROC) plot derived from the linear discriminate analysis (LDA) using blood-based markers based on the top finding from PLS approach. | Translational Psychiatry

Fig. 1: Receiver operating characteristics (ROC) plot derived from the linear discriminate analysis (LDA) using blood-based markers based on the top finding from PLS approach.

From: Precision psychiatry with immunological and cognitive biomarkers: a multi-domain prediction for the diagnosis of bipolar disorder or schizophrenia using machine learning

Fig. 1

a Receiver operating characteristics (ROC) plot derived from the linear discriminate analysis (LDA) using blood-based markers based on the top finding from PLS approach. ROC plot of sensitivity (true positive rate) vs. 1-specificity (false positive rate) based on a LDA build upon the six markers with the highest contribution as determined by the PLS discriminant analysis. b ROC plot derived from the LDA using cognitive markers based on the top finding from PLS approach. ROC plot of sensitivity (true positive rate) versus 1-specificity (false positive rate) based on a LDA build upon the six markers with the highest contribution as determined by the PLS discriminant analysis. c ROC plot derived from the LDA using blood-based markers and cognitive markers based on the top finding from PLS approach. ROC plot of sensitivity (true positive rate) vs. 1-specificity (false positive rate) based on a LDA build upon the six markers with the highest contribution as determined by the PLS discriminant analysis.

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