Infertility treatment using IVF methods requires to the collection, storage and analysis of large quantities of various types of data. Created at the University Hospital in Bialystok, system of electronic registration of information about patients treated for infertility using the IVF ICSI/ET method, turned out to be useful in the process of data collection and storage of information about treated couples. However, it does not satisfy the condition relating to the need to analyze the data collected. For this reason, system developers have taken the trouble of improving it with a statistical module that fulfills hopes connected with it. This module consists of two main parts which generally may be called: descriptive statistics and neural network. The first part of the module refers to the designation and presentation of descriptive statistics. They are based on a number of key features of the treatment process, as well as the juxtaposing the designated statistics, broken down into groups defined by the grouping variables. The second part concerns the neural network to predict the efficacy of the treatment. The network which has been used here provides nearly 90% probability treatment failure and can be used for the prediction of negative cases.
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.