Extended Data Fig. 6: Decision support with the BCC and breast metastases models.
From: Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
For each dataset, slides are ordered by their probability of being positive for cancer, as predicted by the respective MIL-RNN model. The sensitivity is computed at the case level. a, BCC (n = 1,575): given a positive prediction threshold of 0.025, it is possible to ignore roughly 68% of the slides while maintaining 100% sensitivity. b, Breast metastases (n = 1,473): given a positive prediction threshold of 0.21, it is possible to ignore roughly 65% of the slides while maintaining 100% sensitivity.
