Research ArticleCancer

Using deep learning for dermatologist-level detection of suspicious pigmented skin lesions from wide-field images

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Science Translational Medicine  17 Feb 2021:
Vol. 13, Issue 581, eabb3652
DOI: 10.1126/scitranslmed.abb3652

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Finding the odd one out

Early identification of skin cancer is key to improving patient outcome. Soenksen et al. built a deep convolutional neural network that examines lesions from a given patient present in wide-field images, including those taken with cell phone cameras. Rather than evaluate a single lesion at a time looking for predetermined signs of neoplasia, the algorithm identifies lesions that differ from most of the other marks on that patient’s skin, flagging them for further examination and ranking them in order of suspiciousness. The algorithm performed similarly to board-certified dermatologists and could potentially be used at primary care visits to help clinicians triage suspicious lesions for follow-up.

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