摘要：Intrauterine insemination (IUI) is one of many treatments provided to infertility patients. Many factors such as,but not limited to,quality of semen, the age of a woman,and reproductive hormone levels contribute to infertility. Therefore,the aim of our study is to establish a statistical probability concerning the prediction of which groups of patients have a very good or poor prognosis for pregnancy after IUI insemination. For that purpose,we compare the results of two analyses:Cluster Analysis and Kohonen Neural Networks. The k-means algorithm from the clustering methods was the best to use for selecting patients with a good prognosis but the Kohonen Neural Networks was better for selecting groups of patients with the lowest chances for pregnancy.
