Abbreviations: CI: Confidence interval, BCC: Basal cell
carcinoma, SCC: Squamous cell carcinoma, sBCC: Superficial basal cell
carcinoma, nBCC: Nodular basal cell carcinoma, iBCC: Infiltrative basal
cell carcinoma, mnBCC: micronodular basal cell carcinoma.
A fair degree of agreement was shown on this task, with a Cohen’s Kappa
= 0.327 (Supplemental Table 2) . Readers were less accurate in
differentiating SCC from BCC; each reader indicated the presence of SCC
in 7 of 17 specimens containing a histologic SCC component. In addition,
raters overcalled the presence of nodular BCC; they indicated the
presence of this subtype in 54% and 58% of all cases and in those
instances were correct 55.7% and 60.0% of the time (positive
predictive values).
Deep-learning algorithm: Most nBCC regions were
segmented (Figure 4 , Table 2) . The integrated
segmentation and classification model showed better performance than the
segmentation-only model. The artifact of the FOV boundary was
significantly reduced when comparing the results of focal loss and
cross-entropy loss. The false positives on nBCC are significantly
reduced, and the mIOU increased to 60.3%±10.1%. The sensitivity and
specificity reach 93.5%±2.2% and 81.2%±9.2%, respectively.