Visualizing histopathologic deep learning classification and anomaly detection using nonlinear feature space dimensionality reduction.

Routine incorporation of this convenient approach for quantitative visualization and error reduction in histopathology aims to accelerate early adoption of CNNs into generalized real-world applications where unanticipated and previously untrained classes are often encountered.