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.\nThe algorithm would have to be refined and rigorously tested before put to use in the medical world. You don't want a glitch leading to the wrong diagnosis. If and when it's ready for prime time, however, it could do more than save time when you're at the clinic. Ideally, you could use the algorithm on your smartphone -- imagine taking a photo of an unusual mark on your body and getting an initial verdict without leaving home. And since you can train computer vision systems to recognize many object types, you could theoretically apply the technology to other visible conditions.