Knowledge-based temporal abstraction for diabetic monitoring

Proc Annu Symp Comput Appl Med Care. 1994:697-701.

Abstract

We have developed a general method that solves the task of creating abstract, interval-based concepts from time-stamped clinical data. We refer to this method as knowledge-based temporal-abstraction (KBTA). In this paper, we focus on the knowledge representation, acquisition, maintenance, reuse and sharing aspects of the KBTA method. We describe five problem-solving mechanisms that solve the five subtasks into which the KBTA method decomposes its task, and four types of knowledge necessary for instantiating these mechanisms in a particular domain. We present an example of instantiating the KBTA method in the clinical area of monitoring insulin-dependent-diabetes patients.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Artificial Intelligence*
  • Blood Glucose / analysis
  • Diabetes Mellitus, Type 1* / blood
  • Humans
  • Monitoring, Physiologic / methods*
  • Software
  • Time Factors

Substances

  • Blood Glucose