Integrating model-based decision support in a multi-modal reasoning system for managing type 1 diabetic patients

Artif Intell Med. 2003 Sep-Oct;29(1-2):131-51. doi: 10.1016/s0933-3657(03)00045-9.

Abstract

We present a multi-modal reasoning (MMR) methodology that integrates case-based reasoning (CBR), rule-based reasoning (RBR) and model-based reasoning (MBR), meant to provide physicians with a reliable decision support tool in the context of type 1 diabetes mellitus management. In particular, we have implemented a decision support system that is able to jointly exploit a probabilistic model of the glucose-insulin system at the steady state, a RBR system for suggestion generation and a CBR system for patient's profiling. The integration of the CBR, RBR and MBR paradigms allows for an optimized exploitation of all the available information, and for the definition of a therapy properly tailored to the patient's needs, overcoming the single approaches limitations. The system has been tested both on simulated and on real patients' data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artificial Intelligence*
  • Decision Support Systems, Clinical*
  • Diabetes Mellitus, Type 1 / therapy*
  • Disease Management*
  • Humans
  • Probability Theory