Qualitative models and Application to Medical Diagnosis
by Liliana Ironi
in Proc. 9th France-URSS-Italy Joint Symposium in Computational Mathematics and Applications,
INRIA-Sophia Antipolis, (1991),
139-157.
ABSTRACT
Current research in Artificial Intelligence is attempting to develop a
framework for the exploitation of model-based reasoning in a diagnostic
environment.
In some application domains, for example the medical one, where
the knowledge of values of parameters and functional relationships about
variables is often incomplete, a qualitative formulation seems to be more
adequate than a quantitative one because of the reduced number of assumptions
in building the model.
Moreover, for many problems, there might be interest
only in few features, often of qualitative nature, of the solution.
After a brief overview of the existing approaches to qualitative modeling, the
{\bib Qsim} method is described.
Finally, it is discussed how qualitative models and
their simulation results can be exploited in a medical diagnostic expert system
in order to highly enhance its performance.
Back to publication list
Liliana Ironi
June 25th, 1996