Researchers at Stanford University have made a potential breakthrough in the diagnosis of common skin cancers by developing software that is capable of identifying common symptoms and signs. They used a database of 129,450 images to train a deep-learning algorithm to identify 2,032 different skin diseases. This new programming technique mimicks brain function by creating artificial neural networks allowing researchers to ‘teach’ algorithms to identify patterns in training images, and then apply this knowledge to new photos. The resulting algorithm was able to perform at a level on par with 21 expert clinicians over a series of 130,000 tests.
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