<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Infertility is a serious social problem. Very often the only treatment possibility are IVF methods. This study explores the possibility of outcome prediction in the early stages of treatment. The data, collected from the previous treatment cycles, were divided into four subsets, which corresponded to the selected stages of treatment. On each such subset, sophisticated data mining analysis was carried out, with appropriate imputations and classification procedures. The obtained results indicate that there is a possibility of predicting the final outcome at the beginning of treatment.</p></abstract>

Infertility is a serious social problem. Very often the only treatment possibility are IVF methods. This study explores the possibility of outcome prediction in the early stages of treatment. The data, collected from the previous treatment cycles, were divided into four subsets, which corresponded to the selected stages of treatment. On each such subset, sophisticated data mining analysis was carried out, with appropriate imputations and classification procedures. The obtained results indicate that there is a possibility of predicting the final outcome at the beginning of treatment.

Classification Issue in the IVF ICSI/ET Data Analysis: Early Treatment Outcome Prognosis

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

Department of Biology and Pathology of Human Reproduction, Institute of Animal Reproduction and Food Research Polish Academy of Sciences, Olsztyn, Poland

Department of Reproduction and Gynaecological Endocrinology, Medical University of Bialystok, Poland

Studies in Logic, Grammar and Rhetoric

Infertility is a serious social problem. Very often the only treatment possibility are IVF methods. This study explores the possibility of outcome prediction...

Classification Issue in the IVF ICSI/ET Data Analysis: Early Treatment Outcome Prognosis

Published Online: Dec 31, 2013

Page range: 103 - 115

DOI: https://doi.org/10.2478/slgr-2013-0034

This content is open access.