Health at Watson Analyst Day

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It was apparent at the Watson Analyst Day on May 23rd that IBM’s message has been refined over the five years since Jeopardy, and that it has begun to gel. Just as we in the Cognitive Computing Consortium have moved from a vague understanding that we were dealing with a fundamentally new phase in technology, so too has IBM’s understanding of what cognitive computing is, and what it’s good for become much more solid.

A core point of emphasis from IBM centered on the importance of data—curated, annotated data that is normalized in some way using ontologies for both categorization and reasoning. This should come as no surprise to those of us from the online industry, who know that there is no substitute for the blood sweat and tears that go into building a credible, usable collection of information. The question today is how to do this at scale, and at least semi-automatically, using NLP, categorizers, clustering engines, and learning systems, training sets, and whatever other tools we can throw at this barrier to sense making.

By far, the biggest advances in cognitive applications have been made in healthcare. With good reason. Medicine has a long history of information curation. Advances in ontology building, controlled vocabularies (normalization) and categorization date back to the 1950’s. PubMed and its predecessors had already built multilingual online collections of medical publications, clinical data, toxicology, and treatment guidelines as early as the 1980’s.

These resources predate IBM Watson health and have enabled it to address health information problems with an existing, well-curated knowledge base. Healthcare requires extreme accuracy, big data analytics, advanced patient-doctor-machine natural interaction, and a probabilistic approach to solving a medical problem. Because the amount of possibly relevant information is staggering, and the outcome is a matter of life and death, the reasons for investment in cognitive systems are obvious for healthcare insurers and providers alike. There are also, of course, billions of healthcare dollars at stake.

From this perspective, then, IBM’s recent $2.6 billion acquisition of Truven Health Analytics and its multi-millions of patient records is not simply an expensive revenue expansion plan, it’s a fundamental upgrade of Watson Health’s core collection of big data.


About the Author:

Sue Feldman is Co-founder and Managing Director at the Cognitive Computing Consortium. She also is PrAs VP for Content Technologies at IDC, Sue developed and led research on search, text analytics and unified access technologies and markets. Her most recent book, The Answer Machine was published in 2012. Her current research is on use cases and guidelines for adopting cognitive computing to solve real world problems.
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