UNASSIGNED: @entity1489 , the most common @entity1 @entity5 , is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of @entity272 using images is a challenging task owing to the fine-grained variability in the appearance of @entity272 . Deep convolutional neural networks (CNNs) show potential for general and highly variable tasks across many fine-grained object categories. Here we demonstrate classification of @entity272 using a single CNN, trained end-to-end from images directly, using only pixels and disease labels as inputs. We train a CNN using a dataset of 129,450 clinical images-two orders of magnitude larger than previous datasets-consisting of 2,032 different diseases. We test its performance against 21 board-certified dermatologists on biopsy-proven clinical images with two critical binary classification use cases: keratinocyte @entity189 ; and @entity320 versus benign nevi. The first case represents the identification of the most common @entity5 , the second represents the identification of the @entity1489 . The CNN achieves performance on par with all tested experts across both tasks, demonstrating an artificial intelligence capable of classifying @entity1489 with a level of competence comparable to dermatologists. Outfitted with deep neural networks, mobile devices can potentially extend the reach of dermatologists outside of the clinic. It is projected that 6.3 billion smartphone subscriptions will exist by the year 2021 (ref. 13) and can therefore potentially provide low-cost universal access to vital diagnostic care.

Dermatologist-level classification of XXXX with deep neural networks.

@entity1 :: ('9606', 'Species') :: ['human'] @entity5 :: ('MESH:D009369', 'Disease') :: ['cancers', 'malignancy'] @entity1489 :: ('MESH:D012878', 'Disease') :: ['skin cancer', 'Skin cancer', 'deadliest skin cancer'] @entity189 :: ('MESH:D002277', 'Disease') :: ['carcinomas versus benign seborrheic keratoses'] @entity272 :: ('MESH:D012871', 'Disease') :: ['skin lesions'] @entity320 :: ('MESH:D008545', 'Disease') :: ['malignant melanomas']
@entity1489 :: (MESH:D012878,Disease) :: ['skin cancer']
