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Background
Deep‐learning convolutional neural networks (CNNs) have outperformed even experienced dermatologists in dermoscopic melanoma detection under controlled conditions. It remains unexplored how real‐world dermoscopic image transformations affect CNN robustness.
Objectives
To investigate the consistency of melanoma risk assessment by two commercially available CNNs to help formulate recommendations...
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