Utilizing Data Mining Techniques for Investigating Factors Influencing the Failure of Intrauterine Insemination Infertility Treatment

Infertility is one of the problems that has caused a lot of psychological and worldly costs on infertile couples. Intrauterine Insemination (IUI) is one of the medically-Assisted Reproduction Techniques (ART) to help infertile couples to have a successful pregnancy. Because of unpredictable results of this technique، identifying the factors influencing the effectiveness of IUI is important. The aim of this study was to identify factors influencing the failure of IUI using data mining techniques. By utilizing K means algorithm، a descriptive technique of data mining، and Davis-Buldin index، the patients were divided into seven clusters and the features of each cluster were analyzed. Increasing age، overweight، obesity، length and type of infertility in women appeared to be effective factors which were revealed by cluster analysis and investigation of the features of each cluster. Male factors including duration of infertility and spermogram type were other causes of failure in this method of infertility treatment. By analyzing the results of clustering technique، the effective factors in the failure of IUI treatment in infertile couples were identified. The obtained results of clustering technique with the consultant of experts can be used for predicting the result of IUI treatment and helping researchers، physicians and infertile couples to choose the best treatment. [1]. MSc Student of Information Technology، Faculty of Industrial Engineering، K. N Toosi University of Technology، Tehran، Iran; Corresponding Author (faranakabolmasum@yahoo. com) [2]. Assistant Professor of Information Technology Department، Faculty of Industrial Engineering، KN Toosi University Of Technology، Tehran، Iran [3]. MSc of Information Technology Faculty of Industrial Engineering، K. N Toosi University of Technology، Tehran، Iran