Affiliations: [a] Department of Computer Science & Engineering, University of Texas at Arlington, Arlington, TX 76019-0015, USA. E-mail: [email protected], [email protected], [email protected] | [b] Intelligent Technologies Corporation, 11044 Research Blvd., #A-500, Austin, TX 78759, USA | [c] Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75235-9103, USA. E-mail: [email protected]
Note: [*] Department of Computer Science & Engineering, University of Texas at Arlington, PO Box 19015, Arlington, TX 76019, USA. Tel.: +1 817 272 3606; Fax: +1 817 272 3784; E-mail: [email protected]
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.
Keywords: knowledge discovery, data mining, temporal reasoning, machine learning, medical databases
