New systems can scan images to detect disease at ever-earlier stages and forecast illnesses to come. But they would require an overhaul in medical decision-making. Learn more about it in one of our latest articles.
Sign up for our email newsletter for the latest science newsLooking at the mammogram image, with its spiderweb of faint gray lines showing dense breast tissue, you wouldn’t suspect anything was amiss. No human radiologist would hesitate to give this Massachusetts General Hospital patient a clean bill of health. But the Mirai artificial-intelligence system, created at MIT, thinks differently.
But forecasts that AI systems will replace doctors are greatly exaggerated. “It’s not as if people will walk into an MRI scanner and a computer will generate a report,” says Deepak L. Bhatt, an interventional cardiologist and Harvard Medical School professor. “There’ll still be a physician that takes a look at the image and interprets it in the clinical context.” In fact, most doctors actually welcome the prospect of an AI assist as they decide how best to treat each patient.
From this avalanche of data, the systems learn which distinct image features — say, near-imperceptible blemishes cloaked by dense breast tissue in a mammogram — denote disease or predict its emergence. “The model [is] looking only at the image, but looking at it in a sophisticated fashion, learning to use all the subtle patterns that are there,” Yala says.
Since algorithms can detect patterns humans can’t, therefore expediting a doctor’s assessment, AI systems like these could help enable broader national screening programs for lung cancer or heart disease. “It could be a great equalizer for health care,” says University of Virginia urologist Kirsten Greene. “People without access to a top-20 medical center — it won’t matter, because technology will at least try to level the playing field.”But that kind of seismic change won’t happen right away.
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