Exploiting Temporal Relations in Mining Hepatitis Data

Various data mining methods have been developed last few years for hepatitis study using a large temporal and relational database given to the research community. In this work we introduce a novel abstraction method to this study by detecting and exploiting temporal patterns and relations between events in viral hepatitis such as “event A slightly happened before event B and B simultaneously ended with event C”. We developed algorithms to first detect significant temporal patterns in temporal sequences and then to identify temporal relations between these temporal patterns. Many findings by data mining methods applied to transactions/graphs of temporal relations shown to be significant by physician evaluation and matching with published in Medline. Keywords Temporal patterns, temporal relations, hepatitis study.

• Type: Journal
• Year: 2007
• Where: NGC
• Authors: Tu Bao Ho, Canh Hao Nguyen, Saori Kawasaki, Si Quang Le, Katsuhiko Takabayashi
• Keywords: Communications, Hepatitis Study, NGC 2007, Temporal Patterns, Temporal Relations