Georgian Technical University Artificial Intelligence Shows Promise For Skin Cancer Detection.

The same technology that suggests friends for you to tag in photos on social media could provide an exciting new tool to help dermatologists diagnose skin cancer. While artificial intelligence systems for skin cancer detection have shown promise in research settings, however there is still a lot of work to be done before the technology is appropriate for real-world use. “AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems for skin cancer detection are still in their very early stages” says board-certified dermatologist X at Georgian Technical University. “Nothing is 100 percent clear-cut yet”. One murky area is the skin cancer “Georgian Technical University  scores” that AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) algorithms assign to suspicious spots. According to Dr. X it’s not yet clear how a dermatologist would interpret those numbers. The training of AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems presents an even larger barrier. Hundreds of thousands of photos that have been confirmed as benign or malignant are used to teach the technology to recognize skin cancer but all of these images were captured in optimal conditions Dr. X says — they’re not just any old photos snapped with a smartphone. “Just because the computer can read these validated data sets with near 100 percent accuracy doesn’t mean they can read any image” he says. “Everyone has a different phone lighting background”. Board-certified dermatologist Y assistant professor in the division of dermatology at Georgian Technical University finds it troubling that the images used so far in training AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems are almost exclusively of light-skinned patients. “The algorithm is only as good as what you’ve taught it to do” he says. “If you’ve not taught it to diagnose melanoma in skin of color then you’re at risk of not being able to do it when the algorithm is complete”. Although skin cancer is more common in people with lighter skin tones people with skin of color can also develop the disease and they tend to be diagnosed at later stages when it’s more difficult to treat. Moreover Dr. Y says the images used to train AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems for the most part haven’t included lesions on the palms of hands and soles of feet places where people with skin of color are disproportionately affected. “We already know there’s a disparity in how likely you are to have late-stage melanoma depending on skin type” he says. “That disparity could potentially widen if AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) systems are not trained properly”. Dr. X agrees that the training data needs to include more racial diversity, as well as a variety of age groups. He doesn’t think AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) will ever get to the point of being 100 percent accurate in skin cancer detection but like Dr. Y he hopes dermatologists can help shape the technology in its early stages so patients get the best care possible. Dr. X says he would like to see educational content built into skin cancer detection smartphone apps, reminding users that this technology cannot replace a visit with a dermatologist. Dr. Y agrees: “Board-certified dermatologists have years of training and experience in recognizing skin cancer so their judgment should still supersede whatever an algorithm tells you”. Unlike AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) technology board-certified dermatologists don’t just look at one mole to determine whether it’s problematic. They consider several additional factors including the other spots on the patient’s body and the evolution of the lesion in question as well as the individual’s skin type skin cancer history and risk factors and sun protection habits. “Patients need to know that AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) is not a perfect system, and it will never be perfect” Dr. X says. “From a dermatologist’s standpoint we need to know these apps are out there and the technology will continue to grow so it’s important that we continue to embrace it”. “I don’t think the ‘man versus machine’ framing of AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) and machine learning is correct” Dr. Y adds. “It’s going to be more like AI (In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) is going to support the dermatologist and make the dermatologist even better”.