Paging Dr. Watson: Artificial Intelligence As a Prescription for Health Care

IBM’s Watson in the lab in Yorktown Heights, New York. Image: Clockready/Wikimedia Commons
Everyone agrees health care in the United States is a colossal mess, and IBM is betting that artificially intelligent supercomputers are just what the doctor ordered. But some health professionals say robodoctors are just flashy toys.
Such are the deep questions raised by the medical incarnation of Watson, the language-processing, information-hunting AI that debuted in 2011 on the quiz show Jeopardy!, annihilating the best human player ever and inspiring geek dreams of where its awesome computational power might be focused next.
IBM has promised a Watson that will in microseconds trawl the world’s medical knowledge and advise doctors. It sounds great in principle, but the project hasn’t yet produced peer-reviewed clinical results, and the journey from laboratory to bedside is long. Still, some doctors say Watson will be fantastically useful.
“It’s not humanly possible to practice the best possible medicine. We need machines,” said Herbert Chase, a professor of clinical medicine at Columbia University and member of IBM’s Watson Healthcare Advisory Board. “A machine like that, with massively parallel processing, is like 500,000 of me sitting at Google and Pubmed, trying to find the right information.”

Others, including physician Mark Graber, a former chief of the Veterans Administration hospital in Northport, New York, are less enthused.

“Doctors have enough knowledge,” said Graber, who now heads the Society to Improve Diagnosis in Medicine. “In medicine, that’s not the problem we face.”

Chase and Graber embody the essential tensions of applying Watson to healthcare, even if the machine is inarguably a wonder of artificial intelligence. Winning Jeopardy! might seem like a trivial, so to speak, accomplishment, but it was an enormous computational achievements.

Watson wasn’t programmed with the information it needed, but given the cognitive tools necessary to acquire the knowledge itself, teasing out answers to complicated questions from vast amounts of electronic information. And it did this not in response to computer-language queries posed through an arcane interface, but with everyday conversational English.
If Watson could determine, in a fraction of a second, that Paganini’s 24 Capricci set the standard for études on violin, or that hedgehog spines are stiffened by keratin, it was logical to think next of medicine. Why not ask about a patient’s tumor or chest pain, input the relevant medical records and exam results, then turn Watson loose on humanity’s medical textbooks and journal articles, the entirety of which it could analyze in minutes?

After all, doctors make mistakes. Lots of mistakes. Enough to kill about 200,000 Americans annually. Experts put misdiagnosis rates around 10 percent, a number that varies widely by condition but in some situations, such as complicated cancers, goes far higher. Watson’s programmers say the machine might prevent many of those mistakes. It would constantly be updated with the latest medical knowledge, bringing to every doctor insights that often take years to filter out of academia, and merging those insights with each patient’s own data.

“We have all these different dimensions of data about an individual. How do we match the different characteristics they have — personal, medical — with a set of knowledge, of information, that is going to define what the best thing for them to do is?” said Basit Chaudhry, lead research clinician for Watson, at the Wired Health Conference on Oct. 16.

IBM launched partnerships with insurance giant WellPoint and the Sloan-Kettering Cancer Center in New York and is expected offer Watson commercially to hospitals within the next few years. Yet though Watson is clearly a powerful tool, doctors like Graber wonder if it’s the right tool. “Watson may solve the small fraction of cases where inadequate knowledge is the issue,” he said. “But medical school works. Doctors have enough knowledge. They struggle because they don’t have enough time, because they didn’t get a second opinion.”

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