Intelligent Information Systems project : Health-e-Assistant
Despite the huge market, the current healthcare system struggles with a number of issues including determining insurance coverage and medical treatment costs, finding doctors covered by insurance policy, finding expert doctors familiar with the medical condition, and maintaining records of medicines and patient histories. It is also difficult to get basic information such as the locations of registered nurses to take care of patients and the appropriate governmental social-support programs that would provide financial and social benefits.
Currently, there are massive amounts of healthcare information in cyberspace, ranging from government and business maintained resources to Web 2.0 user-generated content, e.g. wikis, blogs, online healthcare discussion groups, etc. However, all this information is not being effectively leveraged because 1) the sources are diverse in syntax, semantics and structural representation; and 2) they are fragmented across an enormously distributed network.
System Overview
Health-e-Assistant is an engine that seeks to lay the foundation for the personalization of healthcare by providing a comprehensive and user-friendly management system that facilitates: 1) the discovery of health-related information e.g. financial, physical, and informative, and social services e.g. transportation programs, financial assistance programs, and in-house support services; 2) the intelligent analysis and delivery of healthcare information based on personalized needs; and 3) the automated acquisition of the social services to help patients manage their medical conditions.
Team: Tyrone Grandison, Christan Grant, Bryan Hickerson, Kun Liu, Evimaria Terzi, Tarun Thakur
Papers:-
Tyrone Grandison, Christan Grant, Kun Liu, varun Bhagwan, Tarun Thakur. "Leveraging Online Data To Deliver Better Decision Support For Personalized Chronic Disease Management", American Medical Informatics Association (AMIA) 2009 Spring Congress. Orlando, Florida. May 28-30, 2009.
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Kun Liu, Tyrone Grandison, Evimaria Terzi, Tarun Thakur. "Optimizing The Delivery Of Social Services", American Medical Informatics Association (AMIA) 2009 Spring Congress. Orlando, Florida. May 28-30, 2009.
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Kun Liu, Evimaria Terzi, Tyrone Grandison. "Highlighting Diverse Concepts in Documents". To appear in the Proceedings of the 2009 SIAM International Conference on Data Mining (SDM 09), April 30-May 2, 2009. Sparks, Nevada.
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Kun Liu, Evimaria Terzi, Tyrone Grandison. "ManyAspects: A System for Highlighting Diverse Concepts in Documents". International Conference on Very Large Data Bases (VLDB). Auckland, New Zealand. August 2008. Demo Paper.
