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      Paula KleinCreated by Paula Klein on Feb 26, 2015 in Public Site: MIT CDB

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      On February 24 I attended a workshop at MIT on the Future of Health Analytics. The event was sponsored by MIT Connection Science, a recently organized research initiative aimed at leveraging data science to quantify and analyze human behaviors, and to leverage the new insights thus obtained in key societal applications, including healthcare, transportation and finance. Connection Science - with which I’m affiliated as a Fellow - was founded by Media Lab professor Alex “Sandy” Pentland.  He’s the author of several books, including the recently published Social Physics: How Good Ideas Spread. 

       

      I’ve worked with Pentland for the past several years, and have previously written about his research on Reinventing Society in the Wake of Big Data, as well as his work with the World Economic Forum and others on the creation of trust frameworks for the sharing and protection of personal data.  In his opening remarks at the workshop, Pentland talked about Big Data and Health. The little data breadcrumbs that we leave behind as we move around in the world can now be reality mined to help us better understand our behaviors and thus improve our lives and health.  He discussed several applications of big data to health, based on research at his MIT Human Dynamics Lab, as well as startups he’s involved in.

      Following Pentland, Dr. Dennis Ausiello talked about Quantitative Human Phenotyping and the opportunities it offers to transform the practice of medicine.  Dr. Ausiello is professor of medicine at the Harvard Medical School, Chief Emeritus of Medicine at Massachusetts General Hospital (MGH), and director and co-founder of the Center for Assessment Technology and Continuous Health (CATCH), a joint MGH-MIT initiative aimed at finding new ways of measuring the human condition, i.e., phenotypes.

       

      What are phenotypes?  According to the National Human Genome Research Institute: “A phenotype is an individual’s observable traits, such as height, eye color, and blood type. The genetic contribution to the phenotype is called the genotype. Some traits are largely determined by the genotype, while other traits are largely determined by environmental factors.” Wikipedia offers a broader definition:  “A phenotype is the composite of an organism’s observable characteristics or traits,… [it] results from the expression of an organism’s genes as well as the influence of environmental factors and the interactions between the two.”  It further adds that whereas the genotype is an organism’s full hereditary information, the phenotype is what that heredity actually produces.

       

      In a recent paper, Dr. Ausiello notes that health analytics has the potential to become the next frontier in medicine, driven by the confluence of three key revolutions:

      • The digital revolution, including all the various mobile devices and associated software and apps that enable us to collect huge amounts of information about an individual’s actual behavior.
      • The genetic revolution, which has identified very large numbers of genetic variations that contribute to human traits and to the risk of disease.
      • The data revolution, which is enabling us to collect, store and analyze extremely large and disparate data sets relevant to human health, yielding insights on individual patients as well as entire populations.

       

      But, he said, achieving this next frontier requires major changes in how medicine is generally practiced. “Our current system of delivering health care is episodic and reactive. That is, patients see their physicians largely at regularly scheduled intervals (typically 1 year) and/or when symptoms appear or worsen… During their episodic appointments, the methods physicians use to assess disease in our patients have largely remained the same for decades. The typical office visit will document the patient’s medical history and symptoms since the last visit (usually several months ago); parameters such as weight, heart rate, blood pressure, and respiratory rate; a physical examination; and perhaps standard blood tests such as general chemistry values and a lipid panel. Whereas, specialized blood diagnostics and imaging studies are used to investigate specific diagnoses, the most commonly used measures reflect an uneasy balance between cost, the time constraints of an office visit, and the ability to detect significant changes in health status.”

       

      Continue reading the full blog, which was posted March 17, here.

      There are still a few spots left to hear MIT IDE co-directors and authors of The Second Machine Age, Erik Brynjolfsson and Andrew McAfee, discuss new research on the digital economy. This event will be held Friday, April 10, at the Congress Centre and will introduce the IDE to supporters and the MIT alumni community in London. Erik will address Employment, Wage Equality and Skills of the Future, while Andy focuses on New Digital Business Models.

       

      The conference (see agenda here) will highlight MIT's role in understanding and shaping the increasingly digital economy and how digital technologies are transforming business, the economy and society.  Specifically, they'll discuss why harnessing the exponential improvements in artificial intelligence, robotics, networks, analytics and digitization is a grand challenge -- and how MIT is responding.

       

      Offering additional insights will be Roberto Rigobon, Professor of Management and Applied Economics on the topic of Reshaping Economic Measurement, and visiting professor, Marshall Van Alstyne, who will discuss the new age of platform economics. Click here to register.

       

      In case you missed last year’s event launching the IDE in New York City, watch some highlights of talks by Andrew McAfee and Erik Brynjolfsson on this video:


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