Communications of the ACM
This AI Could Help Wipe Out Colon Cancer
The U.S. Food and Drug Administration has approved the use of an artificial intelligence system that promises to help doctors recognize precancerous growths during a colonoscopy.
Credit: Getty Images
Michael Wallace has performed hundreds of colonoscopies in his 20 years as a gastroenterologist. He thinks he's pretty good at recognizing the growths, or polyps, that can spring up along the ridges of the colon and potentially turn into cancer. But he isn't always perfect. Sometimes the polyps are flat and hard to see. Other times, doctors just miss them. "We're all humans," says Wallace, who works at the Mayo Clinic. After a morning of back-to-back procedures that require attention to minute details, he says, "we get tired."
Colonoscopies, if unpleasant, are highly effective at sussing out pre-cancerous polyps and preventing colon cancer. But the effectiveness of the procedure rests heavily on the abilities of the physician performing it. Now, the Food and Drug Administration has approved a new tool that promises to help doctors recognize precancerous growths during a colonoscopy: an artificial intelligence system made by Medtronic. Doctors say that alongside other measures, the tool could help improve diagnoses. "We really have the opportunity to completely wipe out colon cancer in anybody who gets screened," says Wallace, who consulted with Medtronic on the project.
The Medtronic system, called GI Genius, has seen the inside of more colons than most doctors. Medtronic and partner Cosmo Pharmaceuticals trained the algorithm to recognize polyps by reviewing more than 13 million videos of colonoscopies conducted in Europe and the US that Cosmo had collected while running drug trials. To "teach" the AI to distinguish potentially dangerous growths, the images were labeled by gastroenterologists as either normal or unhealthy tissue. Then the AI was tested on progressively harder-to-recognize polyps, starting with colonoscopies that were performed under perfect conditions and moving to more difficult challenges, like distinguishing a polyp that was very small, only in range of the camera briefly, or hidden in a dark spot.
From Wired
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