Further, 7 differentially expressed proteins (Table S8 .2A) identified in 2D-DIGE were implicated as potential classifiers for the discrimination of FM and VM patients and healthy subjects employing similar type of analysis ( Figure S9B ). We achieved 95.83% overall prediction accuracy on blinded prediction (n = 23) using PLS-DA. Table S8 .2B summarizes the percentage of the samples classified during model training, cross-validation and independent prediction respectively. In the final validation phase; we achieved 100 and 95.83% overall prediction accuracy with Decision Trees and SVM respectively, followed by Naïve Bayes (91.66%) on blinded prediction using the biomarker dataset for FM (n = 8), VM (n = 7) and HC (n = 8).