Bayesian Belief Network (BBN), one of the data mining classification methods, is
used in this research for mining and analyzing medical track record from a relational data table.
In this paper, a mutual information concept is extended using fuzzy labels for determining the
relation between two fuzzy nodes. The highest fuzzy information gain is used for mining fuzzy
association rules in order to extend a BBN. Meaningful fuzzy labels can be defined for each
domain data. For example, fuzzy labels of secondary disease and complication disease are
defined for a disease classification. The implemented of the extended BBN in a application
program gives a contribution for analyzing medical track record based on BBN graph and
conditional probability tables.