Analyzing Outcomes of Intrauterine Insemination Treatment by Application of Cluster Analysis or Kohonen Neural Networks

Intrauterineinsemination(IUI)isoneofmanytreatmentsprovided toinfertilitypatients.Manyfactorssuchas,butnotlimitedto,qualityofsemen, the age of a woman, and reproductive hormone levels contribute to infertility. Therefore,theaimofourstudyistoestablishastatisticalprobabilityconcerning the prediction of which groups of patients have a very good orpoor prognosis forpregnancyafterIUIinsemination.Forthatpurpose,wecomparetheresults of twoanalyses: Cluster AnalysisandKohonenNeuralNetworks. Thek-means algorithmfromtheclusteringmethodswasthebesttouseforselectingpatients withagoodprognosisbuttheKohonenNeuralNetworkswasbetterforselecting groups of patients with thelowest chances for pregnancy.