RESUMO
Objective To explore the application of association rules with Constraints in medical data analysis.Methods Constraints were applied in mining association rules of medical data by analyzing the characteristics of the data.An effective algorithm for mining association rules with constraints from medical data called CAMD was developed.The algorithm was applied to the analysis ofcoronary heart disease dataset.Results Assigning minimum support and minimum confidence as 0.20 and 0.60,respectively,with data from 303 cases of coronary heart dieses analyzed,8 association rules were tained.Crrelations between age,sex,electrocardiograph results,pathogeny and diagnosis of coronary heart disease were discovered.Conclusion Results from our experiments show that CAMD scans the database fewer times and has no need of pruning candidate itemsets.Thus,it greatly decrease the amount of useless rules produced and rapidly discover interesting association rules of medical data.
