Researchers at Stanford University have created an AI algorithm that can identify skin cancer as well as a professional doctor. The program was trained on nearly 130,000 images of moles, rashes, and lesions using a technique known as deep learning. It was then tested head-to-head against 21 human dermatologists, where its creators say it performed with an accuracy on par with humans ("at least" 91 percent as good). In the future, they suggest it could be used to create a mobile app for spotting skin cancer at home. Each year in the United States, some 5.4 million new cases of skin cancer are diagnosed.
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 knowledge 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 diagnoses that included more than 2,000 diseases.
A new artificial intelligence system can spot the tell-tale signs of skin cancer just as accurately as human doctors, say researchers, and the next step is to get the tech on a smartphone, so anyone can run a self-diagnosis. Once the system is refined further and becomes portable, it could give many more people the chance to get screened with minimal cost, and without having to wait for an appointment with a doctor to confirm the symptoms. The Stanford University researchers behind the deep learning system say the key to its success is an algorithm that enables it to apply what it knows from its existing database of skin cancer samples to pictures it hasn't seen before. "We made a very powerful machine learning algorithm that learns from data," says one of the team, Andre Esteva. "Instead of writing into computer code exactly what to look for, you let the algorithm figure it out."
Artificial intelligence that is as accurate as human specialists at identifying skin cancer has been developed by computer scientists and dermatologists. The breakthrough was made by a team at Stanford University, who trained a deep-learning algorithm to diagnose skin cancer using a database of around 130,000 skin disease images. "We realized it was feasible, not just to do something well, but as well as a human dermatologist," said Sebastian Thrun, a professor at the Stanford Artificial Intelligence Laboratory. A woman covers herself in suncream to stress the point that people should protect themselves from the sun as part of a Cancer Research Campaign, April 8, 1998. Researchers have developed an Artificial Intelligence program that can diagnose skin lesions as accurately as any specialist.
Skin cancer is one of the most common cancers in the world and often the easiest to contract with thanks to the sun. However, scientists have now developed a new kind of technology that can detect skin cancer, literally at the touch of a button. The artificial intelligence (AI) system will soon be available for smartphones everywhere and is said to be just as accurate as a doctor's diagnosis. There are many advantages that come with being able to self-diagnose skin cancer yourself, including saving time, money, and having a better chance of catching it early, with no need to make an appointment to see a doctor. The way in which the system works is by using deep learning techniques that compare sample pictures from an existing database to that of the patient and then give its diagnosis.