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Issue No. 02 - March-April (2012 vol. 32)
ISSN: 0272-1716
pp: 89-95
Y. Livnat , Univ. of Utah, Salt Lake City, UT, USA
T. Rhyne , Univ. of Utah, Salt Lake City, UT, USA
M. Samore , Univ. of Utah, Salt Lake City, UT, USA
Early detection and rapid response to infectious-disease outbreaks rely on effective decision making based on information from disparate sources. To improve decision-making in outbreak detection and response, it's important to understand how public health practitioners seek relevant information. Epinome, a user-centric visual-analytics system, supports research on decision-making in public health, particularly evaluation of information search strategies. Epinome facilitates investigation of scripted high-fidelity large-scale simulated disease outbreaks. Its dynamic environment seamlessly evolves and adapts as the user's tasks and focus change. This video shows how the Epinome system facilitates interactive simulations of disease outbreaks.
Decision making, Diseases, Medical expert systems, Medical information systems, Visualization, Public healthcare, Adaptation models, Search problems

Y. Livnat, T. Rhyne and M. Samore, "Epinome: A Visual-Analytics Workbench for Epidemiology Data," in IEEE Computer Graphics and Applications, vol. 32, no. 2, pp. 89-95, 2012.
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