Medical Doctors will always be Doctors! Artificial Intelligence
will only be another tool enabling physicians to better treat the sick! Oh yeah…It
will save all a boat load of money!
IBM's Watson is better at diagnosing cancer than human
doctors
WIRED
Monday 11 February 2013
IBM's Watson --
the language-fluent computer that beat the best human champions at a game of
the US TV show Jeopardy! -- is being turned into a tool for
medical diagnosis. Its ability to absorb and analyse vast quantities of data
is, IBM claims, better than that of human doctors, and its deployment through
the cloud could also reduce healthcare costs.
The first stages of a planned wider
deployment, IBM's business agreement with the Memorial
Sloan-Kettering Cancer Center in
New York and American private healthcare company Wellpoint will see Watson available for rent to
any hospital or clinic that wants to get its opinion on matters relating to
oncology. Not only that, but it'll suggest the most affordable way of paying
for it in America's excessively-complex healthcare market. The hope is it will
improve diagnoses while reducing their costs at the same time.
Two years ago, IBM announced that Watson had "learned"
the same amount of knowledge as the average second-year medical student. For
the last year, IBM, Sloan-Kettering and Wellpoint have been working to teach
Watson how to understand and accumulate complicated peer-reviewed medical
knowledge relating to oncology. That's just lung, prostate and breast cancers
to begin with, but with others to come in the next few years). Watson's
ingestion of more than 600,000 pieces of medical evidence, more than two
million pages from medical journals and the further ability to search through
up to 1.5 million patient records for further information gives it a breadth of
knowledge no human doctor can match.
According to Sloan-Kettering,
only around 20 percent of the knowledge that human doctors
use when diagnosing patients and deciding on treatments relies on trial-based
evidence. It would take at least 160 hours of reading a week just to keep up
with new medical knowledge as it's published, let alone consider its relevance
or apply it practically. Watson's ability to absorb this information faster
than any human should, in theory, fix a flaw in the current healthcare model.
Wellpoint's Samuel Nessbaum has claimed that, in tests, Watson's successful
diagnosis rate for lung cancer is 90 percent, compared to 50 percent for human
doctors.
Sloan-Kettering's Dr Larry Norton
said: "What Watson is going to enable us to do is take that wisdom and put
it in a way that people who don't have that much experience in any individual
disease can have a wise counsellor at their side at all times and use the
intelligence and wisdom of the most experienced people to help guide
decisions."
The attraction for Wellpoint in all
this is that Watson should also reduce budgetary waste -- it claims that 30 percent of the $2.3 trillion
(£1.46 trillion) spent on healthcare in the United States each year is wasted.
Watson here becomes a tool for what's known as "utilisation
management" -- management-speak for "working out how to do something
the cheapest way possible".
Wellpoint's statement said:
"Natural language processing leverages unstructured data, such as
text-based treatment requests. Eighty percent of the world's total data is
unstructured, and using traditional computing to handle it would consume a
great deal of time and resources in the utilisation management process. The
project also takes an early step into cognitive systems by enabling Watson to
co-evolve with treatment guidelines, policies and medical best practices. The
system has the ability to improve iteratively as payers and providers use
it." In other words, Watson will get better the more it's used, both in
working out how to cure people and how to cure them more cheaply.
When Watson was first devised, it
(or is it "he"?) ran across several large machines at IBM's
headquarters, but recently its physical size has been reduced hugely while its
processing speed has been increase 240 percent. The idea now is that hospital,
clinics and individual doctors can rent time with Watson over the cloud --
sending it information on a patient will, after seconds (or at most minutes),
return a series of suggested treatment options. Crucially, a doctor can submit
a query in standard English -- Watson can parse natural language, and doesn't
rely on standardised inputs, giving it a more practical flexibility.
Watson's previous claim to fame
came from it winning a special game of US gameshow Jeopardy! in 2011. For those unfamiliar, Jeopardy!'s format works like this: the answers
are revealed on the gameboard and the contestants must phrase their responses
as questions. Thus, for the clue "the ancient Lion of Nimrod went missing
from this city's national museum in 2003" the correct reply is "what
is Baghdad?". Clues are often based on puns or other word tricks, and
while it's not quite on the level of a cryptic crossword, it's certainly the
kind of linguistic challenge that would fox most language-literate computers.
Watson's ability to parse texts and
grasp the underlying rules has had its drawbacks, though, as revealed last
month when IBM research scientist Eric Brown admitted that he had tried giving
Watson the Urban
Dictionary as a dataset.
While Watson was able to understand some of the, er, colourful slang that fills
the site's pages, it also failed to understand the different between polite and
offensive speech.
Watson's memory of the Urban
Dictionary had to (regrettably) be wiped.
