<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

Prediction of Infertility Treatment Outcomes Using Classification Trees

Department of Statistics and Medical Informatics, Medical University of Bialystok,

Department of Gamete and Embryo Biology, Institute of Animal Reproduction and Food Research of Polish Academy of Sciences, Olsztyn,

Acacio Fertility Center, Laguna Niguel, California,

Studies in Logic, Grammar and Rhetoric

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Prediction of Infertility Treatment Outcomes Using Classification Trees"}

Infertility is currently a common problem with causes that are often unexplained, which complicates treatment. In many cases, the use of ART methods provides...

Prediction of Infertility Treatment Outcomes Using Classification Trees

Publicado en línea: 23 ene 2017

Páginas: 7 - 19

DOI: https://doi.org/10.1515/slgr-2016-0043

© 2016 Studies in Logic, Grammar and Rhetoric

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.