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projects:ir_biomedical:start

Information Discovery on Biomedical Databases

Involved Researchers

Introduction

As the use of Electronic Medical Records (EMRs) becomes more widespread, so does the need to search and provide effective information discovery on them. Information discovery methods will allow practitioners and other healthcare stakeholders to locate relevant pieces of information in the growing corpus of available EMRs. The success of Web search engines has shown that keyword queries are a useful tool for locating relevant information in an intuitive and effective manner. However, questions arise of the form: What are the semantics of keyword queries on EMRs? What is a meaningful result? What is the role of medical and clinical ontologies and dictionaries like SNOMED (Systematized Nomenclature of Human and Veterinary Medicine) in answering such queries?
In project we tackle problems such as Information Discovery on EMRs using keyword-based queries, and enumerate the salient challenges that must be addressed to facilitate quality information discovery. The objective is to create interest in new medical information management research initiatives, and potentially create new paradigms for using medical data.

Publications

  • Challenges for Information Discovery on Electronic Medical Records.
    Vagelis Hristidis, Fernando Farfán, Redmond P. Burke, Anthony F. Rossi, Jeffrey A. White.
    Book details: Next Generation of Data Mining. CRC - Taylor & Francis. Editors: Hillol Kargupta, Jiawei Han, Philip Yu, Rajeev Motwani, Vipin Kumar. To be released October 2008.
  • Information Discovery on Electronic Medical Records.
    Vagelis Hristidis, Fernando Farfán, Redmond P. Burke, Anthony F. Rossi, Jeffrey A. White.
    National Science Foundation Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM). October 2007.
projects/ir_biomedical/start.txt · Last modified: m/d/Y H:i by ffarfan