MD2K/BD2K

Advancing biomedical discovery and improving health through mobile sensor big data

MD2K  was established as one of 11 national Big Data Centers of Excellence awarded by the National Institutes of Health (NIH) as part of its Big Data-to-Knowledge initiative. The MD2K Center brought together the top brains in Computer Science, Engineering, Medicine, Behavioral Science, and Statistics, drawn from 13 universities (Cornell Tech, Georgia Tech, Harvard, Northwestern, Ohio State,  UCLA, UC San Diego, UC San Francisco, the University of Massachusetts Amherst, the University of Memphis, the University of Michigan, the University of Utah, and West Virginia University). The MD2K Team developed innovative tools to make it easier to gather, analyze and interpret health data generated by mobile and wearable sensors. The goal of the big data solutions being developed by MD2K was to reliably quantify physical, biological, behavioral, social, and environmental factors that contribute to health and disease risk. The research conducted by MD2K aimed to improve the health of individuals through early detection of adverse health events and by facilitating prevention. The MD2K team directly targeted two complex health conditions with high mortality risk – reducing hospital readmission in congestive heart failure (CHF) patients and preventing relapse in abstinent smokers. The approach and product of MD2K is applicable to other complex diseases, such as asthma, substance abuse and obesity. The Center has made the MD2K tools, software, and training materials widely available and organized workshops and seminars to encourage their use by researchers and clinicians.

MD2K Mission

The MD2K Team aimed to lay the scientific foundations for turning the wealth of mobile sensor data available through new and rapidly evolving wearable sensors into reliable and actionable health information, and contribute to the vision of predictive, preventive, personalized, participatory, and precision (P5) medicine.

NIH BD2K Centers

MD2K was  part of the National Institutes of Health (NIH) Big Data to Knowledge (BD2K) initiative, designed to support advances in research, policy, and training that are needed for the effective use of Big Data in biomedical research. As part of this initiative, NIH funded 12 National Centers of Excellence, each representing a multi-investigator, interdisciplinary team working to develop innovative approaches to address a major challenge to the effective use of Big Data. Together, these centers formed a national infrastructure to develop and deploy cutting edge approaches, methods, software, tools, and other resources that enabled biomedical researchers to use Big Data to advance human health. For more information on other current BD2K National Centers of Excellence, please visit the NIH BD2K website.

Grant/Award: NIH-5U54EB020404 
Lead PI: Dr. Santosh Kumar, University of Memphis

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Participating Institutions & Disciplines

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Studies:

Evaluation of the feasibility of a just-in-time intervention to delay or prevent smoking relapse via stress regulation techniques among smokers attempting to quit.

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Evaluation of mobile sensing modalities to automatically detect opioid use and pain flares in a population of individuals experiencing chronic pain.

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Evaluation of the novel EasySense wireless, contactless system in assessing pulmonary congestion via measurements of thoracic impedance and cardiac and lung motion in patients with congestive heart failure (CHF) during hospitalization and post-discharge.

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Examination of the multiple neurocognitive processes that have previously been implicated in relapse among smokers who are both successful and unsuccessful.

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Mobile Sensor Data-to-Knowledge Thrusts

The data science research efforts have been structured into four primary thrust areas: Mobile Sensor Data to Information (MD2I), Mobile Sensor Information to Knowledge (MI2K), MD2K-Implementation, and MD2K-Application.

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Thrust 1: Mobile Sensor Data to Information

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Thrust 2: Mobile Sensor Information to Knowledge

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Thrust 3: MD2K-Implementation

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Thrust 4: MD2K-Application