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.