Induction and Uncertainty Management Techniques Applied to Veterinary
  Medical Diagnosis
  This paper discusses a project undertaken between the Departments of
Computing Science, Statistics, and the College of Veterinary Medicine to design
a medical diagnostic system. On-line medical data has been collected in the
hospital database system for several years. A number of induction methods are
being used to extract knowledge from the data in an attempt to improve upon
simple diagnostic charts used by the clinicians. They also enhance the results
of classical statistical methods - finding many more significant variables. The
second part of the paper describes an essentially Bayesian method of evidence
combination using fuzzy events at an initial step. Results are presented and
comparisons are made with other methods.
