In the latest sign that the singularity is nigh, IBM announced last week that it would start teaching its ultra-fast computer system "Watson" to be something like a robotic radiologist.
The goal is for Watson -- most famous for beating human opponents on "Jeopardy!" -- to be able to interpret medical images from sources such as CT scans, electrocardiograms and MRIs, as well as photographs of skin conditions such as melanoma.
IBM has already started training Watson to analyze visual data -- "to see," the company says. The supercomputer will soon bring this ability to bear on a trove of 30 billion medical images that IBM acquired in its recent $1 billion purchase of health tech company Merge, to figure out how to distinguish a normal result from an abnormal one.
So does that mean that your radiologist cousin could soon be out of a job? That the next time you get an MRI on your bum knee, you'll hear the results in C-3PO's voice?
Not quite. At least not according to radiologists -- admittedly not an unbiased group on this issue.
Dr. John Eng, a radiologist and machine learning expert at Johns Hopkins Hospital, was dubious that Watson will actually be able to compete with a human radiologist when it comes to visual diagnoses anytime soon.
"It seems like the claims are being made that Watson is going to look at images and make general diagnoses from those images and that seems like it's a ways off," he said.
That's because interpreting radiologic images is arguably one of the toughest visual reasoning tasks that humans take on -- far more difficult than, say, identifying a specific person in a photo posted on Facebook. "The human brain is a remarkable pattern recognition machine. It's going to be difficult to beat the brain," said Dr. Daniel Sodickson, the vice chair for research in radiology at the New York University School of Medicine.
But if Watson can't beat radiologists as easily as other "Jeopardy!" contestants, it can join them to assume a key role in patient care.
"As good as we are as radiologists, and as much training as we have, there are still things that we miss on images every day," said Dr. Michael Recht, chair of radiology at the NYU School of Medicine. "And the goal would be to have aids that would help us make sure we wouldn't miss things."
Computers already help radiologists around the country interpret mammograms. Programs highlight potential problem areas on a patient's images, allowing the radiologist who examines them to spend their time most efficiently. And leading radiology departments have also started to adopt similar programs to assist with certain types of CT scans and MRIs -- for example, by tracking the size of abnormal growths more precisely than the human eye is able to.
Watson -- or some other artificial intelligence like Watson -- could, in the not so distant future, take that type of work further and act as a first filter for all sorts of medical images that are later examined by doctors. That could help them catch serious problems that are hard to see with the naked eye. A supercomputer could also act as a kind of second opinion, helping to confirm a doctor's suspicions about a somewhat unusual diagnosis. That, in turn, could cut down on redundant testing, which saves patients time, money and dangerous radiologic exposure.
Watson could serve a particularly crucial role in areas underserved by advanced medicine, suggested Dr. Kimberly Amrami, a musculoskeletal radiologist at the Mayo Clinic in Minnesota.
"If I were a physician in a remote part of sub-Saharan Africa, say, I might have access to a computer, but not a bunch of people with specialized knowledge," she said. "So Watson could serve as a first pass and help determine whether, based on this exam, you need another more advanced, more expensive test, or consultation from an expert far away."
As for the idea that a computer could ever replace radiologists completely, Amrami was highly skeptical. She noted that some people worried about that happening when computer-assisted diagnostics first started to crop up decades ago -- but time has proven them wrong.
"When we went from film to digital, people were worried, but that enhancement in our technology actually made us more important," she said. "So I think that the same will be true here. Watson will only make us better radiologists."
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