Medical data mining on the internet: research on a cancer information system

Andrea L. Houston, Hsinchun Chen, Susan M. Hubbard, Bruce R. Schatz, Tobun D. Ng, Robin R. Sewell, Kristin M. Tolle

Research output: Contribution to journalArticle

28 Scopus citations

Abstract

This paper discusses several data mining algorithms and techniques that we have developed at the University of Arizona Artificial Intelligence Lab. We have implemented these algorithms and techniques into several prototypes, one of which focuses on medical information developed in cooperation with the National Cancer Institute (NCI) and the University of Illinois at Urbana-Champaign. We propose an architecture for medical knowledge information systems that will permit data mining across several medical information sources and discuss a suite of data mining tools that we are developing to assist NCI in improving public access to and use of their existing vast cancer information collections.

Original languageEnglish (US)
Pages (from-to)437-466
Number of pages30
JournalArtificial Intelligence Review
Volume13
Issue number5
StatePublished - Dec 1 1999

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence

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  • Cite this

    Houston, A. L., Chen, H., Hubbard, S. M., Schatz, B. R., Ng, T. D., Sewell, R. R., & Tolle, K. M. (1999). Medical data mining on the internet: research on a cancer information system. Artificial Intelligence Review, 13(5), 437-466.