An event set approach to sequence discovery in medical data

Authors:
Jorge C. G. Ramirez;Diane J. Cook;Lynn L. Peterson;Dolores M. Peterson
Affiliations:
Department of Computer Science & Engineering, University of Texas at Arlington, Arlington, TX 76019-0015, USA and Intelligent Technologies Corporation, 11044 Research Blvd., #A-500, Austin, TX 787 ...;Department of Computer Science & Engineering, University of Texas at Arlington, Arlington, TX 76019-0015, USA. E-mail: {ramirez, cook, peterson}@cse.uta.edu (Tel.: +1 817 2723606/ Fax: +1 817 272 ...;Department of Computer Science & Engineering, University of Texas at Arlington, Arlington, TX 76019-0015, USA. E-mail: {ramirez, cook, peterson}@cse.uta.edu;Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75235-9103, USA. E-mail: dpeter@mednet.swmed.edu
Venue:
Intelligent Data Analysis
Year:
2000

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Abstract

The goal of this research is the discovery of useful concepts in temporal medical databases. Building on previous experiments, we introduce TEMPADIS, the Temporal Pattern Discovery System, which uses an Event Set Sequence approach to discover sequential patterns in medical data. We discuss problems unique to mining medical databases and introduce techniques to overcome some of these problems. Verification results are presented based on a database of Human Immunodeficiency Virus (HIV) patients monitored over four years.