Prediction of Infertility Treatment Outcomes Using Classification Trees

Anna Justyna Milewska; Dorota Jankowska; Urszula Cwalina; Dorota Citko; Teresa Więsak; Brian Acacio; Robert Milewski

doi:10.1515/slgr-2016-0043

Abstract

Infertility is currently a common problem with causes that are often unexplained, which complicates treatment. In many cases, the use of ART methods provides the only possibility of getting pregnant. Analysis of this type of data is very complex. More and more often, data mining methods or artificial intelligence techniques are appropriate for solving such problems. In this study, classification trees were used for analysis. This resulted in obtaining a group of patients characterized most likely to get pregnant while using in vitro fertilization.

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Prediction of Infertility Treatment Outcomes Using Classification Trees

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