Paweł Malinowski, Robert Milewski, Piotr Ziniewicz, Anna Justyna Milewsk, Jan Czerniecki and Sławomir Wołczyński
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.
Paweł Malinowski, Robert Milewski, Piotr Ziniewicz, Anna Justyna Milewska, Jan Czerniecki and Sławomir Wołczyński
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 a more effective analysis of the collected data. This work provides an overview of the new methods used for the analysis of data on infertility treatment, and formulates a proposal for further directions for research into increasing the efficiency of the predicted result of the treatment process.
Paweł Malinowski, Robert Milewski, Piotr Ziniewicz, Anna Justyna Milewska, Jan Czerniecki, Teresa Więsak, Allen Morgan, Dariusz Surowik and Sławomir Wołczyński
One of the most effective methods of infertility treatment is in vitro fertilization (IVF). 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, help to achieve that goal.