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1 Cloud-based Platform for Personalization in a Wellness Management Ecosystem: Why, What, and How Pei-Yun S. Hsueh, Raymund J.R. Lin, Mark J.H. Hsiao, Liangzhao Zeng, Sreeram Ramakrishnan, and
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Document Date: 2012-08-13 11:38:44


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City

Hawthorne / Taipei / Boosting / Cheltenham / New York / Cambridge / Melville / /

Company

MIT Press / IEEE Intelligent Systems / D. S. Group / IBM Taiwan / Case / Forrester Research / /

Country

United Kingdom / Finland / Taiwan / United States / /

Currency

USD / /

Event

FDA Phase / /

Facility

National Institute of Diabetes / IBM T.J. Watson Research Center / /

IndustryTerm

real-time fashion / software deployment / elastic computing capabilities / constant online update / personalization-essential common services / insurance / free trials / risk assessment quality control Online monitoring / in-time services / priority services / data mining algorithms / risk / dedicated computing power / mobile computing / Diabetes Prevention / data transformation services / personalization services / analytics applications / dedicated computing resources / government services / transmission / privacy services / e - commerce / computing / ensemble modeling algorithms / the conversion / data mining community / online data analytics / integrated enterprise services / software vendors / user services / healthcare measure / chronic disease management / required technology components supporting multi-party multi-issue negotiations / wellness management / ecosystem services / wellness analytic services / wellness services / week-day computing / online wellness risk analytics / risk groups / healthcare / Web Service / online setting / match-making recommendable services / technology components / risk stratification services / prior data mining research focuses / analytic services / well developed statistical algorithms / online analytics / personalized intervention services / Diabetes Prevention Program / open platform services / data mining consortium / healthcare services / ecosystem provisioning services / utility computing / personalized services / online learning algorithm / wellness analytics services / pub/sub services / cloud computing / event processing services / open common services / ith risk / web services / /

OperatingSystem

VMs / /

Organization

US Department of Health and Human Services / Ministry of Economic Affairs / National Institute of Diabetes / MIT / Center for Intelligent Information Retrieval / Center of Disease Control / Medical Research Council / World Economic Forum / /

Person

Mark J.H. Hsiao / Edward Elgar / Raymund J.R. Lin / Sreeram Ramakrishnan / Henry Chang / Pei-Yun S. Hsueh / O. Rabin / Liangzhao Zeng / /

Position

family physician / General / representative / case manager / /

Product

RESTful (REpresentational State Transfer) / VMs / SaaS / EECS-2009 / RESTful / /

ProgrammingLanguage

XML / JavaScript / /

ProvinceOrState

New York / Massachusetts / /

PublishedMedium

The R Journal / IEEE Intelligent Systems / Annals of Internal Medicine / Machine Learning / /

Technology

specific algorithm / XML / data warehouse / JSON / API / Quality of Service / corresponding technologies / Service Level Agreement / Jomo technology / virtual machine / HTTP protocol / ensemble modeling algorithms / well developed statistical algorithms / machine learning / online learning algorithm / data mining algorithms / mobile computing / HTTP / data mining / /

URL

http /

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