Better diagnosis with deep convolutional neural networks
“Malignant melanoma is primarily diagnosed visually, beginning with an initial clinical screening,” said Dr Allan Halpern . This step is then followed by dermoscopic analysis, a biopsy and histopathological examination.
Artificial intelligence—deep convolutional neural networks (CNNs) —may help in diagnosis, according to a recent publication . CNNs are feed-forward artificial neural networks and learn the filters that, in traditional algorithms, were hand-engineered. This makes them independent of prior knowledge and human effort.
The working group at Stanford University in California trained this system with a dataset of 129,450 clinical images consisting of 2,032 different diseases (two orders of magnitude larger than previous datasets). The CNN was then tested against 21 board-certified dermatologists on biopsy-proven clinical images.
The result was astonishing: the CNN...
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