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

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Prediction of Infertility Treatment Outcomes Using Classification Trees

Studies in Logic, Grammar and Rhetoric

Volume 47 (2016): Issue 1 (December 2016)

By: Anna Justyna Milewska, Dorota Jankowska, Urszula Cwalina, Dorota Citko, Teresa Więsak, Brian Acacio and Robert Milewski

Open Access

|Jan 2017

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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DOI: https://doi.org/10.1515/slgr-2016-0043 | Journal eISSN: 2199-6059 | Journal ISSN: 0860-150X

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Language: English

Page range: 7 - 19

Published on: Jan 23, 2017

Published by: University of Białystok

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© 2017 Anna Justyna Milewska, Dorota Jankowska, Urszula Cwalina, Dorota Citko, Teresa Więsak, Brian Acacio, Robert Milewski, published by University of Białystok
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 47 (2016): Issue 1 (December 2016)