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FutureMed: Big Data and exponential technologies

February 14th, 2012 |  Published in Big Data  |  2 Comments








14 February 2012 – Last week we had a chance to attend FutureMed, a health-care program that is part of Singularity University, a networked organization dedicated to exploring how disruptive technologies can sweep across whole industries and society.   This came on the heels of LegalTech 2012 in New York which every year addresses isues concerning machine data, information technology and information management.

The subject at this year’s FutureMed was the high-tech future of health care. The technologies on display were impressive, often inspiring — like the wearable-robots, or mechanical exoskeletons, made by Ekso Bionics, to enable people with spinal cord injuries to walk again; or IBM’s Watson question-answering computer that is being morphed into a doctors’ smart assistant.  It is just a series of fast-changing technologies including biotechnology, nanotechnology, robotics, artificial intelligence — all due to the surge in analytics surrounding “Big Data”.   Or as Dr. Daniel Kraft, executive director of the FutureMed program, said:  “There are exponential technologies are all around us”.

Dr. Martin Kohn, chief medical scientist at IBM research, sketched out the future path in health care for the technology behind Watson, the computer that last year outwitted the best human players of Jeopardy!   Quote that brought the crowd to tears of laughter: “You’ll not be surprised to learn that the executive leaders of IBM fairly quickly decided that playing Jeopardy! was not a long-term business model.”

It was at Text Analytics World last year where we saw two brilliant presentations by IBM.  One was on their Watson project and the work they are doing on analyzing vast volumes through natural language processing (NLP), and information retrieval (IR) for applications in business intelligence, enterprise knowledge management, e-discovery, etc..  The second was on the algorithms at the heart of predictive analytics for NLP and IR (which they noted have been around for years) that are moving into the mainstream and how they are successfully applying it to all levels of analysis at the enterprise level: financial, legal and BI.

And at FutureMed it was more of the same (the core transferable technology) albeit at a higher level.  Dr. Kohn explained that it was the artificial intelligence software that made it possible for Watson to read and understand 200 million digital pages, and deliver an answer within three seconds. In health care, Dr. Kohn said, “we are overwhelmed by information. And we’re only as good as what we know.”  No, Watson is not going to make diagnoses (afterall, we have Dr House for that) but will make suggestions, recommendations and determine probabilities. The more information Watson is fed, Dr. Kohn said, the more it learns and understands, in its way.

And it’s “star” turn:  medical complexity.  Determining treatment regimens for patients with more than one chronic condition (such patients account for a large share of the nation’s health care costs).  We have well-defined treatment guidelines for individual conditions like heart disease, diabetes, asthma and emphysema. But the guidelines are far less helpful for patients with more than one condition.  For example, a beta-blocker drug is good for heart disease, but bad for asthma, Dr. Kohn noted. What are the trade-offs and what are the probabilities?

The key, the powerful tool that is Watson?  making more decisions based on data and a surer grasp of the relevant scientific evidence — so-called evidence-based medicine — instead of experience and intuition.  Brilliant technology and we’ll have more on it later this year. 






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"The mind that lies fallow but a single day sprouts up follies that are only to be killed by a constant and assiduous culture."
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