Fig. 3From: Development and validation of a clinic machine-learning nomogram for the prediction of risk stratifications of prostate cancer based on functional subsets of peripheral lymphocyteDiagram of the clinic-ML nomogram and the clinic nomogram. The clinic-ML nomogram (g) is converted from the ML nomogram (e) via FMA (f) which extracts the feature importance (d) from ML models (b) trained on patients’ records with clinical features (a). The clinic nomogram (h) is constructed directly based on clinical features (a)Back to article page