Smart Industry 1/2016

Smart Business IBM Watson
At CeBIT 2016
in Hanover German
chancellor Angela
Merkel got a quick
lesson in cognitive
computing from the
head of IBM Germany,
Martina Koederitz.
telligent enough to teach itself and
reach new conclusions without being
told what to do by human programmers.
“Learning computers” such as Watson
or Google’s AlphaGo are designed
as self-teaching systems that
use data mining, pattern recognition
and natural language processing
to mimic the way the human
brain works. The goal is to create automated
IT systems that are capable
of solving problems without requiring
human assistance.
In addition to the new business centers,
IBM also announced additional
application programming interfaces
(APIs) for its IoT practice in areas
such as machine learning and image
analytics. These include:
Natural Language Processing (NLP),
an application designed to let users
interact with systems and devices
using simple language; solutions
that understand the intent of human
language by correlating it with
other sources of data to put it into
context in specific situations. For
example, a technician working on
a machine might notice an unusual
vibration. He can ask the system
“What is causing that vibration?”. Using
NLP and other sensor data, the
system will automatically link words
to meaning and intent, determine
Dr. Watson Will See You Now
■ Memorial Sloan-Kettering Cancer
Center, New York City
More than 14 million Europeans are diagnosed
with cancer each year, and finding the right
information on each patient to be able to manage
their disease with any degree of success is a huge
challenge. Filtering countless health websites for
relevant, accurate and trustworthy information
is daunting, as is drawing insights from multiple
sources, not to mention advances and discoveries
12
in molecular biology and genetics in recent years.
Together with the Memorial Sloan-Kettering Cancer
Center in New York City, IBM hopes to revolutionize
how physicians get access to world-class
information about cancer. The two organizations
are combining IBM’s Watson’s natural language
processing and machine learning capabilities with
Memorial Sloan-Kettering’s clinical knowledge and
repository of cancer case histories. The goal is to
develop a decision support tool that can help physicians
everywhere arrive at individualized cancer
diagnostic and treatment recommendations for
their patients based on the most complete and
up-to-date information.
Watson is billed as a “self-learning system”. This
means that after receiving an initial query, it can
ask for additional information to help it understand
more precisely what the human wants to know.
Also, physicians can view the logic and evidence
upon which Watson makes a recommendation.
Watson uses the patient’s medical information
combined with a vast array of medical information
gathered from the Internet and other sources,
such as an extensive library of medical literature,
diagnosis and treatment guidelines, a database of
MSK cancer cases and the institution’s knowledge
management system. Watson, its creators maintain,
will be able to learn from its encounters with
clinicians. It will also get smarter as it amasses
more information and correlates treatments with
outcomes.
If the team working on the Watson-based solution
is successful in developing an effective decision
support tool, physicians anywhere could potentially
have access to the knowledge of some of the field’s
top experts–and more cancer patients could get
better care no matter where they live in the world.