dermatology
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AI outperforms human doctors in spotting skin cancer
In January last year scientists reported that artificial intelligence was almost as effective at identifying skin cancer as dermatologists. Now, less than 18 months later, it's even better. In an experiment between a deep learning convolutional neural network (or CNN) and 58 dermatologists, researchers found that human dermatologists accurately identified 86.6 percent of skin cancers from a range of images, compared to 95 percent for the CNN.
AI is nearly as good as humans at identifying skin cancer
If you're worried about the possibility of skin cancer, you might not have to depend solely on the keen eye of a dermatologist to spot signs of trouble. Stanford researchers (including tech luminary Sebastian Thrun) have discovered that a deep learning algorithm is about as effective as humans at identifying skin cancer. By training an existing Google image recognition algorithm using over 130,000 photos of skin lesions representing 2,000 diseases, the team made an AI system that could detect both different cancers and benign lesions with uncanny accuracy. In early tests, its performance was "at least" 91 percent as good as a hypothetically flawless system.
Light Bandage treats skin cancer on-the-go
A physicist and a dermatology consultant at the University of St. Andrews in Scotland (no, that's not the beginning of a joke) have just built a new revolutionary mobile treatment for skin cancer. Their invention is a "light bandage" whose LEDs shine onto the affected area while the wearer is out and about, and draws power from an iPod-sized battery pack. The device is based on the principles of photodynamic therapy treatment (PDT), which is traditionally used to treat skin cancer; however, in current applications of PDT, patients must sit or lie still while sitting under huge light sources. Of course, this means that now you can go lay on the beach to get your tan on, absorbing ultraviolet rays while wearing a light bandage to treat your skin cancer. Perfect.[Via medGadget]
