Abstract
This paper describes a methodology for representing and using medical knowledge about
temporal relationships to infer the presence of clinical events that evolve over time.
The methodology consists of three steps: (1) the incorporation of patient observations
into a generic physiologic model, (2) the conversion of model states and predictions
into domain-specific temporal abstractions, and (3) the transformation of temporal
abstractions into clinically meaningful descriptive text. The first step converts
raw observations to underlying model concepts, the second step identifies temporal
features of the fitted model that have clinical interest, and the third step replaces
features represented by model parameters and predictions into concepts expressed in
clinical language. We describe a program, called TOPAZ, that uses this three-step
methodology. TOPAZ generates a narrative summary of the temporal events found in the
electronic medical record of patients receiving cancer chemotherapy. A unique feature
of TOPAZ is its use of numeric and symbolic techniques to perform different temporal
reasoning tasks. Time is represented both as a continuous process and as a set of
temporal intervals. These two temporal models differ in the temporal ontology they
assume and in the temporal concepts they encode. Without multiple temporal models,
this diversity of temporal knowledge could not be represented.
Key-Words
Symbolic Data Interpretation - Physiological Models and Simulation - Computer-Based
Problem Solving - Temporal Reasoning and Representation
