Temporal abstraction from temporal clinical databases using inference graphs

Abstract

Temporal abstraction (TA) methods aim to extract more meaningful data from raw temporal data. The use of temporal abstraction is important for decision support applications which consume abstract concepts, while databases usually contain primitive concepts. In this paper we propose a new approach for TA from temporal clinical databases: using inference graph, an extension of transition graph, as an implementation technique of a knowledge-based temporal abstration system. The approach has been applied to the clinical database system for monitoring the treatment of patients who have colorectal cancer. © 2006 IEEE.