Planned acquisition to help IBM Watson ‘see’ medical images
IBM last week announced that Watson will gain the ability to “see” medical images through the planned acquisition of Merge Healthcare Inc.
“As a proven leader in delivering healthcare solutions for over 20 years, Merge is a tremendous addition to the Watson Health platform,” said John Kelly, senior vice president, IBM Research and Solutions Portfolio. “Healthcare will be one of IBM’s biggest growth areas over the next 10 years, which is why we are making a major investment to drive industry transformation and to facilitate a higher quality of care. Watson’s powerful cognitive and analytic capabilities, coupled with those from Merge and our other major strategic acquisitions, position IBM to partner with healthcare providers, research institutions, biomedical companies, insurers and other organizations committed to changing the very nature of health and healthcare in the 21st century. Giving Watson ‘eyes’ on medical images unlocks entirely new possibilities for the industry.”
According to Robert McMillan and Elizabeth Dwoskin writing in today’s Wall Street Journal, “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.”
IBM said medical images represent by far the largest and fastest growing data source in the healthcare industry and perhaps the world, with radiologists in some hospital emergency rooms viewing an estimated 100,000 images per day. IBM’s strategy is to combine rich image analytics with deep learning to enable the Watson Health platform to analyze and cross-reference medical images against a trove of lab results, electronic health records, genomic tests, clinical studies, and other data sources.
“As Watson evolves, we are tackling more complex and meaningful problems by constantly evaluating bigger and more challenging data sets,” Kelly said. “Medical images are some of the most complicated data sets imaginable, and there is perhaps no more important area in which researchers can apply machine learning and cognitive computing. That’s the real promise of cognitive computing and its artificial intelligence components—helping to make us healthier and to improve the quality of our lives.”
McMillan and Dwoskin in the Journal note that training software to produce a diagnosis requires huge numbers of images. They quote Kelly as saying, “The way these machine-learning engines work, the more you feed them the smarter they get.”
They also write, “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.”
They cite one example: “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.”
One difficulty is getting hospitals to provide access to archives of anonymized images. They quote Enlitic’s CEO, Jeremy Howard, as saying, “People are starting to realize these archives have value. Before, these images were sitting around for 25 years gathering dust.”
