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Subject:
From:
Tammie Dudley <[log in to unmask]>
Reply To:
MS Student <[log in to unmask]>
Date:
Thu, 7 Apr 2011 13:18:28 -0400
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Departmental Colloquium Announcement
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Title: Splash: A Computational Platform for Collaborating to Solve 
Complex Health Problems
Speakers: Paul P. Maglio and Cheryl A. Kieliszewski IBM Research - Almaden
Date: Thursday, April 14, 2011
Time: 2:00pm - 3:30pm
Location: 34 Peachtree Street, 14th Floor Conference room

--------------------
Abstract
The Smarter Planet Platform for Analysis and Simulation of Health 
(Splash) is a novel computational framework for integrating independent 
data, models, and simulations to create comprehensive system models for 
understanding individual and population health at multiple scales and 
for multiple purposes. Health results from complex interactions among 
many distinct human, environment, and social systems, such as cultural, 
educational, political, and economic conditions, as well as policies, 
practices, costs, and pricing in industries as diverse as advertising, 
transportation, agriculture, and others. Interventions and policies 
aimed at improving population health by affecting one system may have 
serious and unanticipated consequences in another. Chronic conditions 
such as obesity have resisted medical, behavioral, and policy 
interventions that touch a single system, for instance solely at the 
level of biology, psychology, community, built environment, economic 
investment, or public policy. We do not always think through the 
interactions among such systems. It is difficult to do. It requires 
cross-domain thinking and systems thinking, and also careful 
collaboration among experts in different domains to explore complex 
interdependencies among the operation of the real-world systems each 
expert knows best. This is where Splash can help—by supporting 
collaborations among those with health-related data, models, and 
problems through an open systems-based platform capable of integrating 
disparate data, models, and simulations, each representing parts of the 
broader health system. The goal is to create an interoperating complex 
composite system model supporting what-if analyses by policy makers. In 
this talk, we will outline the overall vision of Splash and describe our 
progress so far, focusing on a proof-of-concept demo that combines four 
models and several datasets to examine alternative policies to reduce 
population obesity in a hypothetical community. We will discuss our 
experiences, lessons learned, and ongoing challenges.

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