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Google is getting really, really good at recognizing photos and videos of cats. All it took was supplying millions of examples so that the company’s software—based on a branch of artificial intelligence called deep learning—could start recognizing the difference between cats and other furry creatures. But Jeremy Howard wants to use deep learning for something a little more practical: diagnosing illnesses. And he’s finally getting his chance.
Today Howard’s company, Enlitic, said it was going to start working with Capitol Health Limited, a radiology clinic with locations across Australia, to have its software look at X-rays.
Enlitic won’t replace radiologists. Instead, the software is designed to help them do their jobs more quickly and make fewer mistakes. First, it checks each file submitted to make sure the image matches what the technicians say it’s supposed to be—for example, it makes sure that if an image is tagged as a left knee that it’s not actually a right knee. Then, it looks for anomalies in the image.
Depending on what it finds, it assigns a priority to the X-ray and routes it to a radiologist. For example, if it finds nodules on an image of a pair of lungs, it will assign it a high-priority status and route it to a pulmonary radiologist. If it detects what appears to be an aneurysm, it will route the X-ray to a cardiovascular radiologist instead. If it finds no anomalies, it will mark it as low priority. After a radiologist has reviewed the image, the software will help write the paperwork by auto-generating text for some of the more tedious parts of a report.
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More Deep Learning
Enlitic’s X-ray algorithms are just the latest example of deep learning being put to practical use. Facebook is now using deep learning techniques to caption photos for the blind. Yelp recently explained how it’s using deep learning to optimize what photos it shows on restaurant listings. And similar techniques are also part of what powers Microsoft’s Skype Translate.
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And Enlitic isn’t the only company trying to apply artificial intelligence to medicine. IBM’s Watson has been used for research at Memorial Sloan-Kettering Cancer Center and more recently to provide diet and exercise advice. The app Bright.md aims to help physicians speed up routine appointments. But Enlitic’s deal appears to be one of the biggest real-world tests of deep learning’s ability to aid medical diagnostics.
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Eventually, Howard hopes the technology will help expand access to medical diagnostics as Capital Health begins opening clinics in Asia. He cites World Economic Forum report that forecasts a severe shortage of medical experts in the developing world if training programs aren’t accelerated. With any luck, artificial intelligence can shoulder some of that burden.