יובל שחר

Physicians and medical decision-support applications, such as for diagnosis, therapy, monitoring, quality assessment, and clinical research, reason about patients in terms of abstract, clinically meaningful concepts, typically over significant time periods. Clinical databases, however, store only raw, time-stamped data. Thus, there is a need to bridge this gap. We introduce the Temporal Abstraction Language (TAR) which enables specification of abstract relations involving raw data and abstract concepts, and use it for defining typical medical
abstraction patterns. For each pattern we further analyze finiteness properties of the answer set. The TAR language is implemented as