A data mining application in medicine

Recently biomedical sciences, biology and medicine have undergone tremendous advances in their technologies and therefore have generated huge amounts of biomedical information and data sets. It seems impossible to analyze this amount of data obtained. Since medical and biological data are vital for patients minimum error rates in diagnosis, therapy and prognosis levels are required. Therefore it shall be easy and extremely fast to reach previous and recent data analysis in medical databases and construction of decision support systems is crucial. Computers are appropriate solutions. Nevertheless a method is required to turn all these information and data to expressive knowledge and to expose the secret meanings of the collected data mass. Data mining is the optimum solution method to reach these goals.In this thesis study, application fields of data mining in medicine, knowledge discovery processes in databases, data mining, association rules in data mining and Apriori algorithm is discussed.A survey study was held to obtain data about migraine disease in Sakarya University. Random surveyors of academic and administrative staff of Sakarya University participated in the study. Association rules were sought by the help of Apriori algorithm, one of the most common algorithms used in related applications. A web based software was developed in ?.net? platform to apply Apriori algorithm. This software enables monitoring the processing levels of the algorithm step by step. At the end of study projected association rules are acquired.Key Words: Data Mining, Medical Data Mining, Clinical Data Mining, Apriori Algorithm, Association Rules