Machine Learning for Predicting Hyperglycemic Cases Induced by PD-1/PD-L1 Inhibitors

Figure 6

Predictive evaluations in terms of ROC curves. in ROC curves, prediction from single items (“reactions,” “reason,” “country,” “weight,” “year,” “age,” “priority” and “sex”) “stay” around diagonal with low area under curve (AUC), while prediction from model (red line) nearly at top in (a∼f). In (g∼h), the single variable did not “stay” around diagonal, maybe because of the influence by limited positive case (only 1); but red lines were still at the top. The predictive performances were much better improved from this model than any single variables. (a) Avel (test part). (b) Dur (test part). (c) Atez (test part). (d) Pem (test part). (e) Nivo (test part). (f) Ipi. (g) Cem. (h) Cam.