Figure 4.

Integrating SPOKE enhances classifier AUC. ROC curves for predicting MS diagnosis at year(s) −1, −3, and −5 (A–C accordingly) with a random forest classifier. The classifiers that used encounters from All-Visits are in blue (SPOKEsig input vector) and green (SPOKE Entry Point [SEP] input vector). The classifiers that only used encounters from primary care provider (PCP) visits are shown in orange (SPOKEsig input vector) and red (SEP input vector). In all instances the SPOKEsig input vectors out preformed the corresponding SEP input vector. The largest gain in AUC was for the PCP encounter classifier 3 years prior to diagnosis.