ABSTRACT
This chapter introduces the representation of temporal information. It deals with patients' data, which are intrinsically temporal. The chapter also deals with the representation of clinical temporal knowledge for data interpretation. It discusses the representation of temporal constraints about the actions in the clinical guidelines. The chapter also introduces some reasoning mechanisms on temporal information. It provides some temporal constraint propagation mechanisms that can be exploited to provide some useful temporal facilities to the users of the clinical guideline systems. The chapter explains the basic framework of Simple Temporal Problems and how Simple Temporal Problems are extended and exploited to provide temporal facilities. It also provides a general discussion on the main temporal reasoning frameworks in Artificial Intelligence. The chapter reviews the main approaches to clinical temporal abstraction. Clinical records are usually stored in relational databases and, since clinical data are intrinsically temporal, temporal information is fundamental information to be stored.
