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Could smartphones be used to detect skin cancer?
Possibly. A recent study in the journal Nature found that computers programmed with image recognition technology could diagnose skin cancer just as accurately as skilled skin cancer doctors looking at the same images.
Training a computer to look for skin cancer
These doctors, known as dermatologists, are trained to look for signs of skin cancer, including melanoma, the deadliest form of skin cancer. They often use the ABCDE system to assess features on skin to distinguish between a regular mole and a cancerous mole.
Stanford University researchers “trained” a computer to diagnose skin cancer by classifying digital images of skin lesions. They provided the computer with nearly 130,000 labelled images of skin lesions. These images covered more than 2,000 skin diseases. The more images they provided to the computer, the better it got at making a diagnosis.
Diagnosing skin cancer using artificial intelligence
The researchers then tested how precise the computer was at identifying skin cancer. They gave the computer previously unseen skin lesion images and asked whether the lesions needed further medical attention. They showed the same set of images to a group of skilled dermatologists.
The computer did as well or better than the doctors in accurately distinguishing between cancerous and non-cancerous skin lesions.
In fairness to the doctors, the researchers did not test whether the doctors were better at diagnosing skin disease using traditional physical skin exams instead of only digital images.
This study isn’t the only example of using artificial intelligence in making medical decisions for cancer. A hospital in Florida is using the IBM super computer Watson, best known for beating Jeopardy champion Ken Jennings, to interpret clinical information of cancer patients to identify the best treatment options.
Studying the possibility of the technology
Before you start searching for the smartphone app, more research needs to be done before it can be made more widely available. Can the computer distinguish between similar-looking skin diseases? Would it be helpful with decision-making in the clinic? How would it fare when faced with the full spectrum of skin lesions seen in the clinic?
Yet, the possibilities of this current study are profound. It offers an effective, cheap and easy way for doctors and patients to track skin lesions and detect cancer earlier. This is extremely important, since the survival rate for melanoma is less than 20% when it spreads to other organs or distant skin areas. The potential for this research and its implications on the future of early cancer detection are tremendous.
Kelly Fathers, PhD