Prediction of Infertility Treatment Outcomes Using Classification Trees

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 the only possibility of getting pregnant. Analysis of this type of data is very complex. More and more often, data mining methods or artificia...

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Main Authors: Milewska Anna Justyna, Jankowska Dorota, Cwalina Urszula, Citko Dorota, Więsak Teresa, Acacio Brian, Milewski Robert
Format: Article
Language:English
Published: Sciendo 2016-12-01
Series:Studies in Logic, Grammar and Rhetoric
Online Access:https://doi.org/10.1515/slgr-2016-0043
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spelling doaj-4220cbb75bcc4747a50425417e87187b2021-09-05T14:00:42ZengSciendoStudies in Logic, Grammar and Rhetoric0860-150X2199-60592016-12-0147171910.1515/slgr-2016-0043slgr-2016-0043Prediction of Infertility Treatment Outcomes Using Classification TreesMilewska Anna Justyna0Jankowska Dorota1Cwalina Urszula2Citko Dorota3Więsak Teresa4Acacio Brian5Milewski Robert6 Department of Statistics and Medical Informatics, Medical University of Bialystok, Poland Department of Statistics and Medical Informatics, Medical University of Bialystok, Poland Department of Statistics and Medical Informatics, Medical University of Bialystok, Poland Department of Statistics and Medical Informatics, Medical University of Bialystok, Poland Department of Gamete and Embryo Biology, Institute of Animal Reproduction and Food Research of Polish Academy of Sciences, Olsztyn, Poland Acacio Fertility Center, Laguna Niguel, California, United States of America Department of Statistics and Medical Informatics, Medical University of Bialystok, PolandInfertility 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.https://doi.org/10.1515/slgr-2016-0043
collection DOAJ
language English
format Article
sources DOAJ
author Milewska Anna Justyna
Jankowska Dorota
Cwalina Urszula
Citko Dorota
Więsak Teresa
Acacio Brian
Milewski Robert
spellingShingle Milewska Anna Justyna
Jankowska Dorota
Cwalina Urszula
Citko Dorota
Więsak Teresa
Acacio Brian
Milewski Robert
Prediction of Infertility Treatment Outcomes Using Classification Trees
Studies in Logic, Grammar and Rhetoric
author_facet Milewska Anna Justyna
Jankowska Dorota
Cwalina Urszula
Citko Dorota
Więsak Teresa
Acacio Brian
Milewski Robert
author_sort Milewska Anna Justyna
title Prediction of Infertility Treatment Outcomes Using Classification Trees
title_short Prediction of Infertility Treatment Outcomes Using Classification Trees
title_full Prediction of Infertility Treatment Outcomes Using Classification Trees
title_fullStr Prediction of Infertility Treatment Outcomes Using Classification Trees
title_full_unstemmed Prediction of Infertility Treatment Outcomes Using Classification Trees
title_sort prediction of infertility treatment outcomes using classification trees
publisher Sciendo
series Studies in Logic, Grammar and Rhetoric
issn 0860-150X
2199-6059
publishDate 2016-12-01
description 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.
url https://doi.org/10.1515/slgr-2016-0043
work_keys_str_mv AT milewskaannajustyna predictionofinfertilitytreatmentoutcomesusingclassificationtrees
AT jankowskadorota predictionofinfertilitytreatmentoutcomesusingclassificationtrees
AT cwalinaurszula predictionofinfertilitytreatmentoutcomesusingclassificationtrees
AT citkodorota predictionofinfertilitytreatmentoutcomesusingclassificationtrees
AT wiesakteresa predictionofinfertilitytreatmentoutcomesusingclassificationtrees
AT acaciobrian predictionofinfertilitytreatmentoutcomesusingclassificationtrees
AT milewskirobert predictionofinfertilitytreatmentoutcomesusingclassificationtrees
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