Experiments Using Belief Functions and Weights of Evidence incorporating
  Statistical Data and Expert Opinions
  This paper presents some ideas and results of using uncertainty management
methods in the presence of data in preference to other statistical and machine
learning methods. A medical domain is used as a test-bed with data available
from a large hospital database system which collects symptom and outcome
information about patients. Data is often missing, of many variable types and
sample sizes for particular outcomes is not large. Uncertainty management
methods are useful for such domains and have the added advantage of allowing
for expert modification of belief values originally obtained from data.
Methodological considerations for using belief functions on statistical data
are dealt with in some detail. Expert opinions are Incorporated at various
levels of the project development and results are reported on an application to
liver disease diagnosis. Recent results contrasting the use of weights of
evidence and logistic regression on another medical domain are also presented.
