Fig. 3: Model performances in the binary recurrence classification using patient demographics, medical history, and tumor characteristics.
From: Prediction of early-stage melanoma recurrence using clinical and histopathologic features
a AUC and PPV in internal validation (first row) and external validation (second row) when experimenting on the original cohorts (MGB: 215 recurrences vs. 666 non-recurrences; DFCI: 95 recurrences vs. 340 non-recurrences). b AUC and PPV in internal validation (first row) and external validation (second row) when experimenting on the core complete cohorts: negative or not indicated regional lymph node histology, known mitotic rate, and known ulceration (MGB: 142 recurrences vs. 410 non-recurrences; DFCI: 74 recurrences vs. 317 non-recurrences). The best model performance among SVM, RF, GB, MLP, and LR models is specified below each plot.
