Computing Community Consortium Blog

The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.

“Watson Turns Medic”

August 27th, 2012 / in Research News / by Erwin Gianchandani

New Scientist published an interesting story last week describing how Watson — the IBM question-answering supercomputer that bested the world’s leading human competitors on Jeopardy! in February 2011 — is blazing new trails in medicine, learning how to help doctors diagnose patients:

JEOPARDY! IBM Challenge [photo courtesy AP/JEOPARDY! Productions].IT IS more than a year since Watson, IBM’s famous supercomputer, opened a new frontier for artificial intelligence by beating human champions of the quiz show Jeopardy!. Now Watson is learning to use its language skills to help doctors diagnose patients.


Progress is most advanced in cancer care, where IBM is working with several US hospitals to build a virtual physicians’ assistant. “It’s a machine that can read everything and forget nothing,” says Larry Norton, a doctor at the Memorial Sloan-Kettering Cancer Center in New York, who is collaborating with IBM.


When playing Jeopardy!Watson analysed each question in a bid to guess what it was about. Then it looked for possible answers in its database, made up of sources such as encyclopaedias, scoring each according to the evidence associated with it and answering with the highest rated answer. The system takes a similar approach when dealing with medical questions, although in this case it draws on information from medical journals and clinical guidelines.

The New Scientist piece references work published in the journal Artificial Intelligence earlier this month (following the link):

To test the system, Watson was first tasked with answering questions taken from Doctor’s Dilemma, a competition for trainee doctors that takes place at the annual meeting of the American College of Physicians. Watson was given 188 questions that it had not seen before and achieved around 50 percent accuracy — not bad for an early test, but hardly ideal (Artificial Intelligence,


To improve, Watson is now absorbing records — tens of thousands at Sloan-Kettering alone — of treatments and outcomes associated with individual patients. Given data on a new patient, Watson looks for information on those with similar symptoms, as well as the treatments that have been the most successful. The idea is it will give doctors a range of possible diagnoses and treatment options, each with an associated level of confidence. The result will be a system that its creators say can suggest nuanced treatment plans that take into account factors like drug interactions and a patient’s medical history…

Read the rest of the story — including some details about a separate but related venture exploring the idea of training Watson as a financial advisor — on the New Scientist website.

(Contributed by Erwin Gianchandani, CCC Director)

“Watson Turns Medic”

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