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1

Clinical department information system’s internal structure

100%
Ziniewicz P., Malinowski P., Milewski R., Mnich S. Z., Wołczyński S.
Studies in Logic, Grammar and Rhetoric
|
2011
|
issue 25(38)
191-200
EN
The construction of an advanced information system supporting the work of a clinic is a great challenge. Particularly, after the initial determination of the functionality of the system, its internal structure must be designed. For the major elements of the system their interaction must be also accurately determined.
2

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

86%
Malinowski P., Milewski R., Ziniewicz P., Milewsk A. J., Czerniecki J., Wołczyński S.
Studies in Logic, Grammar and Rhetoric
|
2013
|
vol. 35
|
issue 1
103-115
EN
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.
3

Nearest neighbor concept in the study of IVF ICSI/ET treatment effectiveness

86%
Milewski R., Malinowski P., Justyna Milewska A., Czerniecki J., Ziniewicz P., Wołczyński S.
Studies in Logic, Grammar and Rhetoric
|
2011
|
issue 25(38)
49-58
EN
The effectiveness of IVF ICSI/ET infertility treatment depends on many factors. Their identification and classification of individual cases remains a difficult task. This paper presents application of feature selection algorithm MSIMBAF2 and associated kNN classifier to analyze the data set containing results of the infertility treatment process.
4

The Use of Data Mining Methods to Predict the Result of Infertility Treatment Using the IVF ET Method

86%
Malinowski P., Milewski R., Ziniewicz P., Milewska A. J., Czerniecki J., Wołczyński S.
Studies in Logic, Grammar and Rhetoric
|
2014
|
vol. 39
|
issue 1
67-74
EN
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.
5

Classification of Patients Treated for Infertility Using the IVF Method

72%
Malinowski P., Milewski R., Ziniewicz P., Milewska A. J., Czerniecki J., Więsak T., Morgan A., Surowik D., Wołczyński S.
Studies in Logic, Grammar and Rhetoric
|
2015
|
vol. 43
|
issue 1
49-59
EN
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.
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