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  1. Graphical representation of the realtionships between qualitative variables concerning the process of hospitalization in the gynaecological ward using correspondence analysis.Anna Justyna Milewska, Dorota Jankowska, Urszula Górska, Robert Milewski & Sławomir Wołczyński - 2012 - Studies in Logic, Grammar and Rhetoric 29 (42).
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  • Classification issue in the ivf icsi/et data analysis: Early treatment outcome prognosis.Paweł Malinowski, Robert Milewski, Piotr Ziniewicz, Anna Justyna Milewsk, Jan Czerniecki & Sławomir Wołczyński - 2013 - Studies in Logic, Grammar and Rhetoric 35 (1):103-115.
    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 (...)
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  • Analyzing Outcomes of Intrauterine Insemination Treatment by Application of Cluster Analysis or Kohonen Neural Networks.Anna Justyna Milewska, Dorota Jankowska, Urszula Cwalina, Teresa Więsak, Dorota Citko, Allen Morgan & Robert Milewski - 2013 - Studies in Logic, Grammar and Rhetoric 35 (1):7-25.
    Intrauterine insemination 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 (...)
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  • Significance of Discriminant Analysis in Prediction of Pregnancy in IVF Treatment.Anna Justyna Milewska, Dorota Jankowska, Urszula Cwalina, Dorota Citko, Teresa Więsak, Brian Acacio & Robert Milewski - 2015 - Studies in Logic, Grammar and Rhetoric 43 (1):7-20.
    Many factors play an important role in prediction of infertility treatment outcome. The purpose of this study was to identify a set of variables that could fulfill criteria for prediction of pregnancy in IVF patients through the application of data mining – using the discriminant analysis method. The principle of this method is to establish a set of rules that allows one to place multi-dimensional objects into one of two analyzed groups. Six hundred and ten IVF cycles were included in (...)
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  • The Use of Principal Component Analysis and Logistic Regression in Prediction of Infertility Treatment Outcome.Anna Justyna Milewska, Dorota Jankowska, Dorota Citko, Teresa Więsak, Brian Acacio & Robert Milewski - 2014 - Studies in Logic, Grammar and Rhetoric 39 (1):7-23.
    Principal Component Analysis is one of the data mining methods that can be used to analyze multidimensional datasets. The main objective of this method is a reduction of the number of studied variables with the mainte- nance of as much information as possible, uncovering the structure of the data, its visualization as well as classification of the objects within the space defined by the newly created components. PCA is very often used as a preliminary step in data preparation through the (...)
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  • Comparison of Artificial Neural Networks and Logistic Regression Analysis in Pregnancy Prediction Using the In Vitro Fertilization Treatment.Robert Milewski, Anna Justyna Milewska, Teresa Więsak & Allen Morgan - 2013 - Studies in Logic, Grammar and Rhetoric 35 (1):39-48.
    Infertility is recognized as a major problem of modern society. Assisted Reproductive Technology is the one of many available treatment options to cure infertility. However, the efficiency of the ART treatment is still inadequate. Therefore, the procedure’s quality is constantly improving and there is a need to determine statistical predictors as well as contributing factors to the successful treatment. There is a concern over the application of adequate statistical analysis to clinical data: should classic statistical methods be used or would (...)
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  • The Use of Data Mining Methods to Predict the Result of Infertility Treatment Using the IVF ET Method.Paweł Malinowski, Robert Milewski, Piotr Ziniewicz, Anna Justyna Milewska, Jan Czerniecki & Sławomir Wołczyński - 2014 - Studies in Logic, Grammar and Rhetoric 39 (1):67-74.
    The IVF ET method is a scientifically recognized infertility treat- ment method. The problem, however, is this method’s unsatisfactory efficiency. This calls for a more thorough analysis of the information available in the treat- ment process, in order to detect the factors that have an effect on the results, as well as to effectively predict result of treatment. Classical statistical methods have proven to be inadequate in this issue. Only the use of modern methods of data mining gives hope for (...)
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  • Classification of Patients Treated for Infertility Using the IVF Method.Paweł Malinowski, Robert Milewski, Piotr Ziniewicz, Anna Justyna Milewska, Jan Czerniecki, Teresa Więsak, Allen Morgan, Dariusz Surowik & Sławomir Wołczyński - 2015 - Studies in Logic, Grammar and Rhetoric 43 (1):49-59.
    One of the most effective methods of infertility treatment is in vitro fertilization. Effectiveness of the treatment, as well as classification of the data obtained from it, is still an ongoing issue. Classifiers obtained so far are powerful, but even the best ones do not exhibit equal quality concerning possible treatment outcome predictions. Usually, lack of pregnancy is predicted far too often. This creates a constant need for further exploration of this issue. Careful use of different classification methods can, however, (...)
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