By Robert McMillan And Elizabeth Dwoskin
IBM is moving from helping hospitals run smoothly to lending a
hand in the examination room.
International Business Machines Corp.'s planned acquisition of
Merge Healthcare Inc., which sells systems that help doctors store
and access medical images, is a crucial step in its plan to put
artificial intelligence to use in medicine. IBM announced the $700
million deal last week.
Merge's crown jewels are 30 billion images, including X-rays,
computerized tomography, and magnetic-resonance-imaging scans, that
IBM intends to use to "train" its Watson software to identify
ailments such as cancer and heart disease. The resulting services,
it hopes, will help doctors diagnose and treat patients more
effectively and efficiently.
Google Inc., Yahoo Inc.'s Flickr unit and others use similar
software to identify objects in photos. IBM is betting that the
same technology that recognizes cats can identify tumors and other
signs of diseases. The nascent effort could help IBM capture a
larger slice of the $7.2 trillion spent world-wide annually on
health care.
IBM's deal also could reshape the $3 billion market for
archiving medical images and breathe life into companies devoted to
computer-driven interpretation of images. It highlights the value
of such imagery, which typically is anonymized and shared by
hospitals for research purposes, as the software technique known as
deep learning becomes more prevalent in medicine.
Deep learning, a technique in which software learns to identify
patterns by sifting through large amounts of data, has proved
successful at interpreting photographs, improving voice recognition
in smartphones and detecting fraud in financial transactions.
Identifying a tumor involves similar pattern-recognition
techniques, according to John Kelly, senior vice president of IBM's
solutions portfolio and research.
In the long run, IBM and others in the field hope such systems
can become reliable advisers to radiologists, dermatologists and
other practitioners who analyze images--especially in parts of the
world where health-care providers are scarce. But medical scans of
the human body are complex.
"In medical data, there's lots of ambiguity and lots of
fuzziness," said John Eng, an associate professor of radiology at
Johns Hopkins University. "It's kind of messy data, and I think
that's going to be a limiting factor with what IBM does with
Watson."
The effort is in a very early stage. Johns Hopkins is using
computers to help doctors identify tumors in chest scans and
mammograms, but the benefits of existing software tools are limited
and radiologists still largely work without computerized
assistance.
"It's a way off to have a general diagnostic machine," said Dr.
Eng.
IBM has made health care a strategic target of its Watson
platform, an assortment of artificial-intelligence software at the
heart of several of the company's business initiatives.
It aims to pioneer a new category of software products that mine
data for medical insights, which it could sell to large health-care
organizations where it already has relationships.
To that end, it has been testing Watson with researchers at
Cleveland Clinic and New York's Memorial Sloan Kettering Cancer
Center. Acquiring Merge brings not only access to the company's
image archive but also its account list of 7,500 hospitals.
"The access to these clinical relationships and the data is
valuable," said Kevin Hobert, the CEO of Carestream Health Inc., a
Merge competitor.
While IBM hopes Watson will learn to interpret Merge's images,
it also expects the combination of imagery, medical records and
other data to reveal patterns relevant to diagnosis and treatment
that a human physician may miss, ushering in an era of
computer-assisted care. Two other recent IBM acquisitions, Phytel
Inc. and Explorys Inc., yielded 50 million electronic medical
records.
Smaller companies devoted to automated interpretation of medical
imagery felt the impact of IBM's arrival immediately.
Enlitic Inc., a San Francisco-based startup with $5 million in
angel and seed funding, claims that its software identified
malignant lung tumors in X-rays 50% more accurately than a panel of
four radiologists.
The company's CEO, Jeremy Howard, spent the past year
approaching hospitals and clinics for access to anonymized images
that would demonstrate his system's utility.
After IBM's announcement on Thursday, his email inbox brimmed
with messages from hospitals offering images, hospital networks
interested in trying his technology, and radiology services looking
to improve their own accuracy, he said.
Training such software requires huge numbers of images. Merge's
30 billion MRIs are only a start for IBM. "The way these
machine-learning engines work, the more you feed them the smarter
they get," IBM's Mr. Kelly said.
But such imagery remains limited by regulations and industry
reluctance to share what may be sensitive personal information.
Enlitic's Mr. Howard has been approaching hospitals and clinics one
by one to persuade them to share their archives.
"People are starting to realize these archives have value," Mr.
Howard said. "Before, these images were sitting around for 25 years
gathering dust."
Write to Robert McMillan at Robert.Mcmillan@wsj.com and
Elizabeth Dwoskin at elizabeth.dwoskin@wsj.com
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