In view of the current medical data mining process

the medical data mining problems

proposes a mining algorithm based on association rules of medical data

searching through frequent itemsets of medical data

generate strong association rules

the calculated average value and standard deviation of large medical data sets

implementation the association rules adjustment

determine the medical data attributes

construct the appropriate fitness function

according to the classification attribute combination value of fitness function selection

crossover and mutation reduction

calculation of information entropy on classification attribute reduction

classification and attribute information gain by calculating the expected information

the establishment of decision tree mining model

implementation of medical data mining. The experimental results show that the proposed algorithm can effectively improve the level of medical data preprocessing

and the effect of data mining is better.