Artificial
Intelligence System Matches Dermatologists at
Skin Cancer Diag**sis
As many jobs are disappearing to automation, the latest profession to also start seeing the future may be dermatology. Stanford University researchers have developed a deep convolutional neural network, an
Artificial Intelligence technique for building a k**wledge set, to learn how to spot suspect
Cancer lesions.
Today this process is manual and prone to errors of subjectivity.
Dermatologists simply look through a dermatoscope and judge based on their education and experience. The Stanford
System was given 130,000 images of
Skin lesions simply labeled with previously established diag**ses that included more than 2,000 diseases. The
System processed these images and learned on its own what to look for.
To test whether it was a good student, the
System was pitted against 21 board-certified
Dermatologists that were asked to tell apart*kerati**cyte carci**mas, a common type of cancer, from benign seborrheic keratoses and malignant mela**mas, the deadliest cancer, from*benign nevi. And here’s the lowdown on the results according to the study abstract in
Nature: “The CNN [convolutional neural network] achieves performance on par with all tested experts across both tasks, demonstrating an
Artificial Intelligence capable of classifying
Skin Cancer with a level of competence comparable to dermatologists.”
It seems it should be easy to **w create a smartphone app that uses the
System to do the very thing at the point of care and at low cost.
Study in
Nature:
Dermatologist-level classification of skin cancer with deep neural networks…
Via:*
Stanford…
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Artificial Intelligence System Matches Dermatologists at Skin Cancer Diag**sis appeared first on
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