Image-scanning software developed at Stanford University can distinguish deadly skin cancers from benign ones as accurately as top dermatologists, according to a study published Wednesday.<\/p>\n
<\/p>\n
The potentially life-saving technology could soon be incorporated in a smart phone, the researchers said, an advance reminiscent of the diagnostic device wielded by Dr McCoy in the 1960s Star Trek sci-fi series.<\/p>\n
Adapting a Google algorithm designed to distinguish between categories of objects based on images \u2014 telling a cat from a dog, for example \u2014 the Stanford team compiled a database of nearly 130,000 photos of skin disease.<\/p>\n
To be effective, the software would need to tell a benign lesion from a malignant carcinoma.<\/p>\n
Computer scientists \u201ctrained\u201d the algorithm to combine visual processing with a type of artificial intelligence called deep learning.<\/p>\n
From the very outset, the results were startlingly good.<\/p>\n
\u201cThat\u2019s when our thinking changed,\u201d said senior author Sebastian Thrun, a professor in the Stanford Artificial Intelligence Laboratory.<\/p>\n
\u201cWe said, \u2018Look, this is not just a class project for students; this is an opportunity to do something great for humanity\u2019.\u201d<\/p>\n
Fine-tuned with the help of physicians, the app they created performed just as well as a panel of 21 board-certified dermatologists, the researchers reported in the science journal Nature.<\/p>\n
In the United States alone, more than five million new cases of skin cancer are diagnosed every year.<\/p>\n
For melanoma detected in its earliest stages, the five-year survival rate is about 97 percent. If the disease is uncovered only later, that drops to about 14 percent.<\/p>\n
Dermatologists inspect skin for signs of cancer, relying on their training and experience.<\/p>\n
If a lesion is spotted, the next step is typically a closer look with a hand-held microscope called a dermatoscope.<\/p>\n
If doubt remains, the final phase of diagnosis is a biopsy \u2014 taking a skin sample to be tested in a lab.<\/p>\n
The images used in the new app \u2014 representing over 2,000 different skin diseases \u2014 were gathered from the internet and vetted by dermatologists.<\/p>\n
\u201cThere\u2019s no huge dataset of skin cancer, so we had to make our own,\u201d said Brett Kuprel, co-author and Stanford graduate student.<\/p>\n
In a final contest, the app was pitched against 21 dermatologists to identify cancerous and non-cancerous lesions in over 370 images.<\/p>\n
Human and machine performed equally well.<\/p>\n
The next step is to create a smart phone version, the researchers said.<\/p>\n
\u201cEveryone has a supercomputer in their pockets with a number of sensors in it, including a camera,\u201d noted co-lead author Andre Esteva, also a graduate student.<\/p>\n
A smart phone app of this kind \u201cmight enable effective, easy and low-cost medical assessments of more individuals than is possible with existing medical-care systems,\u201d Sancy Leachman of Oregon Health and Science University and Glenn Merlino of the US National Cancer Institute wrote in a comment also published in Nature.<\/p>\n
\u201cStar Trek presented a vision of the future in which (McCoy) used a portable diagnostic device known as a tricorder, to assess the medical condition of Captain James Kirk and other Enterprise crew members.<\/p>\n
\u201cAlthough fanciful then, machines capable of the non-invasive diagnosis of human disease are becoming a reality,\u201d they added.\u2014AFP<\/p>\n
Image: Alamy<\/p>\n","protected":false},"excerpt":{"rendered":"
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