Model-Based Interpretation of Time-Varying Medical Data

Temporal concepts are critical is medical therapy-planning. If given early enough, specific therapeutic choices may abort or suppress evolving undesired changes in a patient’s clinical status. Effective medical decision making demands recognition and interpretation of complex temporal changes that permeate the medical record. This paper presents a methodology for representing and using medical knowledge about temporal relationships to infer the presence of clinically relevant events, and describes a program, called TOPAZ, that uses this methodology to generate a narrative summary of such events. A unique feature of TOPAZ is the use of numeric and symbolic modeling techniques to perform temporal reasoning tasks that would be difficult to encode and perform using only one modeling methodology