Dwpd Y Combinator s quest for diversity
Utilizing machine learning, a Stanford team, including Udacity Sebastian Thrun, was able to match the accuracy of dermatologists at identifying skin cancer.聽The classifier the group b
stanley tumbler uilt is in no way a panacea offering people a precise and irrefutable cancer diagnoses. But even matching fallible human accuracy, the model could pave the way for a less costly, highly-scaleable, solution to get more people taking life-saving preliminary screenings.The team聽started with聽an existing convolutional neural network architecture, previously trained on 1.28 million images from the聽ImageNet dataset. Afterwords, they utilized transfer lean
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stanley romania inical images covering 2,000 different diseases. Over 18 online repositories were used to build the training dataset聽alongside Stanford University Medical Center. Our system requires no hand-crafted features; it is trained end-to-end directly from image labels and raw pixels, wi Ymqe Don 038; Alex Tapscott | INNOVATE 2016
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