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2013 | 35 | 1 | 7-25
Article title

Analyzing Outcomes of Intrauterine Insemination Treatment by Application of Cluster Analysis or Kohonen Neural Networks

Title variants
Languages of publication
EN
Abstracts
EN
Intrauterine insemination (IUI) is one of many treatments provided to infertility patients. Many factors such as, but not limited to, quality of semen, the age of a woman, and reproductive hormone levels contribute to infertility. Therefore, the aim of our study is to establish a statistical probability concerning the prediction of which groups of patients have a very good or poor prognosis for pregnancy after IUI insemination. For that purpose, we compare the results of two analyses: Cluster Analysis and Kohonen Neural Networks. The k-means algorithm from the clustering methods was the best to use for selecting patients with a good prognosis but the Kohonen Neural Networks was better for selecting groups of patients with the lowest chances for pregnancy.
Keywords
Publisher
Year
Volume
35
Issue
1
Pages
7-25
Physical description
Dates
published
2013-12-01
online
2013-12-31
Contributors
  • 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
author
  • Department of Statistics and Medical Informatics, Medical University of Bialystok, Poland
author
  • Shore Institute for Reproductive Medicine, Lakewood, USA
  • Department of Statistics and Medical Informatics, Medical University of Bialystok, Poland
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.doi-10_2478_slgr-2013-0041
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