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. Author manuscript; available in PMC: 2023 Jan 1.
Published in final edited form as: J Invest Dermatol. 2021 Jul 13;142(1):97–103. doi: 10.1016/j.jid.2021.06.015

Figure 2. Performance of proposed method and comparison with a consensus panel of human experts.

Figure 2.

95% CI calculated via bootstrapping. a) Stack-level performance on the MSKCC dataset. The algorithm (N=259 stacks), reported as a ROC curve, achieved an AUC of 90.1. The experts (N=131 stacks) achieved a sensitivity of 77.4%, (95% CI: 67.3% - 87.3%) and a specificity of 65.2% (95% CI: 53.7% - 76.6%). b) Lesion-level performance on the MSKCC dataset. The algorithm (N=62 lesions) achieved an AUC of 90.0%. The experts (N=32 lesions) obtained a sensitivity of 89.5% (95% CI: 73.6% - 100%) and a specificity of 38.5% (95% CI: 12.5% - 64.3%). c) Generalization performance on an external dataset. N=53 stacks. The proposed algorithm achieved an AUC of 86.1%.