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  1. 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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