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 (...) Networks. The k-means algorithm from the clustering methods was the best to use for selecting patients with a good prognosis but the Kohonen Neural Networks was better for selecting groups of patients with the lowest chances for pregnancy. (shrink)

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 (...) creation of independent components for further analysis. We used the PCA method as a first step in analyzing data from IVF (in vitro fertilization). The next step and main purpose of the analysis was to create models that predict pregnancy. Therefore, 805 different types of IVF cy- cles were analyzed and pregnancy was correctly classified in 61-80% of cases for different analyzed groups in obtained models. (shrink)

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 (...) it be more appropriate to apply advanced data mining technologies? By comparing two statistical models, Multivariable Logistic Regression analysis and Artificial Neural Network it has been demonstrated that Multivariable Logistic Regression analysis is more suitable for theoretical interest but the Artificial Neural Network method is more useful in clinical prediction. (shrink)

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. (shrink)

Infertility is a huge problem nowadays, not only from the medical but also from the social point of view. A key step to improve treatment outcomes is the possibility of effective prediction of treatment result. In a situation when a phenomenon with more than 2 states needs to be explained, e.g. pregnancy, miscarriage, non-pregnancy, the use of multinomial logistic regression is a good solution. The aim of this paper is to select those features that have a significant impact on achieving (...) clinical pregnancy as well as those that determine the occurrence of spontaneous miscarriage. Two multi-factor models were obtained, used in predicting infertility treatment outcomes. One of the models enabled to conclude that the number of follicles and the percentage of retrieved mature oocytes have a significant impact when prediction of treatment outcome is made on the basis of information about oocytes. The other model, built on the basis of information about embryos, showed the significance of the number of fertilized oocytes, the percentage of at least 7-cell embryos on day 3, the percentage of blasts on day 5, and the day of transfer. (shrink)

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. (shrink)

The aim of this article was to prepare a basis for further quantitative research concerning the nutritional knowledge of medical professionals (doctors) and dieticians in view of the accuracy of dietary recommendations given to patients. For this purpose, a review of literature data in this area was performed and logical fallacies were proposed as the ‘tool’ that doctors rely on in cases when they lack the proper knowledge required to be able give an informed and beneficial recommendation. In the course (...) of the study, it was found that nutritional education is neglected in medical curricula, while dieticians are underused as professionals in clinical settings. Furthermore, numerous characteristics of the medical profession and the doctor–patient relationship are conducive to committing several types of logical fallacies, prompted mainly by the need for providing advice without delay and the infallibility traditionally expected from doctors. Hence, the gaps in nutritional knowledge and the fallacious character of recommendations, in addition to the re-valuation of the role of the nutritionist, need to be further investigated in order to improve the quality of patient advice in the area of dietary requirements as well as to propose the necessary changes in curricula. (shrink)

Approx. 60–80 million couples globally are affected by the problem of infertility. The issue is important both for the couple trying to conceive and for the whole society in which the couple lives. Lifestyle, including nutrition, may have both a positive and a negative impact on the outcomes of infertility treatment. The aim of this paper is to assess the relationship between knowledge in the area of fertility diet and its actual use, and types of fertility disorders among women undergoing (...) treatment in a fertility clinic. A group of women was analyzed statistically, divided into 3 groups according to their couple’s cause of infertility – the causes of infertility were described as: the male factor, the female factor, and the idiopathic factor. The study group answered questions that comprised a fertility diet knowledge test; the frequency of consumption of particular food products in a individual groups was also analyzed. Correspondence analysis showed differences between the groups in the number of points scored in the fertility diet knowledge test, as well as in the consumption of sweets, crisps and sticks, and nuts and seeds. Women among whom the main cause of infertility was defined as the male factor scored the highest numbers of points in the fertility diet knowledge test, women with the idiopathic cause of infertility scored slightly lower numbers of points, while women whose main cause of infertility was defined as the female factor scored the lowest numbers of points. Women from couples with idiopathic infertility consumed sweets, crisps and sticks the most often, followed by women with the cause of infertility identified on their side, with the lowest frequency of consumption of sweets identified among women whose partner was infertile. Nuts and seeds were consumed the most frequently by women whose partners were infertile, followed by women with the cause of infertility identified on their side, while women with the idiopathic cause of infertility consumed nuts and seeds the least frequently. These examples show that correspondence analysis is well suited to the assessment of the influence of lifestyle on fertility; in addition, it makes it possible to recognize certain correlations that may not be observed in standard statistical tests. (shrink)

Obtaining a sufficient amount of measurable and reliable results of student surveys has always posed a challenge for university teams tasked with the provision of the quality of education. This is especially visible at faculties where education is based on the classic classroom-based model, which then transfers to clinical units, hospital wards, and specialist laboratories. The highly unpredictable pandemic situation caused by the SARS-CoV-2 virus raises the bar for the evaluation of didactics. Fortunately, the continuous technological progress in the area (...) of Artificial Intelligence makes it possible to design the implementation of tools that would improve the position of systems for the management of courses of studies. The evaluation survey for didactic classes, as one of the last output data obtained during the process, may finally become a fully recognized source of information about the conducted classes and the teachers themselves. On the other hand, it may become a tool for those surveyed to influence the quality of classes, express their opinion, present suggestions and propositions generally pertaining to changes in the process of education. New information technologies not only make it possible to improve the effectiveness of reaching the recipients, but also provide completely new, very reliable methods of acquisition of credible behaviour, used as integration data in solutions based on machine communication. Using Artificial Intelligence coupled with data may make it possible to use intelligent communication for effective management of the process of surveying – a solution that has so far been used in business, in the form of the so-called bots. As a result, this would lead to an ongoing, fully quantitative and qualitative, assessment of classes. (shrink)

The paper presents a comparison of the two most commonly used diagnostic tests for orthorexia – ORTO-15 Questionnaire and BOT (Bratman Orthorexia Test) – that use data-mining methods. Orthorexia nervosa is perceived as a new, unclassified eating disorder, which is characterized with pathological fixation on the consumption of healthy foods. In order to assess the coherence of the aforementioned tests, a method from the data-mining group, i.e. correspondence analysis, was used in addition to traditional statistical methods. On the basis of (...) the obtained results, only average correlation between ORTO-15 Questionnaire and BOT test was found. More cases of orthorexia were diagnosed with the use of ORTO-15 Questionnaire, which may result from its higher sensitivity. It was also noted that the coherence of tests increases with increasing BMI values, despite no relationship between BMI and the presence of orthorexia having been proved. Diagnosis of an orthorexia case with the use of BOT test implies that there is a high probability that it will also be diagnosed with the use of ORTO-15 test, but not necessarily the other way around. The performed correspondence analysis confirmed a not very strong coherence of the results of both tests. (shrink)

Log-linear analysis is a practical tool for examining relationships, successfully applied in many fields of science. This paper discusses the topic of estimation of the chance of getting pregnant in couples that underwent ART insemination. The authors focus on finding significant interactions between variables, on the basis of which statistical models are built. With the use of results of log-linear analysis, a model predicting the chances of achieving a clinical pregnancy that contained interactions was successfully built. Moreover, it was more (...) complete than the model obtained with the use of logistic regression alone. (shrink)

Infertility is a global problem affecting 48 to 186 million couples of reproductive age. In Poland, it concerns approx. 1.5 million couples, which amounts to 20% of the population capable of reproducing. One of the factors influencing the incidence of fertility disorders may be lifestyle, understood as a multi-disciplinary accumulation of everyday behaviours and habits. In the study, a group of 201 young adults, students of medical and related faculties, were surveyed in order to check the actual level of knowledge (...) about the impact of lifestyle on reproductive health. The Kohonen network, which is an example of a self-learning neural network, was used to find non-obvious connections between the data. The trained Kohonen neural network formed 4 clusters with different characteristics. Based on analyses of the structure of each cluster, it was found that 2nd year students of Medicine are internally divided into 3 fractions. The first fraction declared a high level of knowledge, but did not have real knowledge. The second fraction was aware of their ignorance, as confirmed by the knowledge test. The last fraction was characterized by a high level of self-confidence regarding their knowledge about reproductive health and obtained a high result in the knowledge test. It was confirmed that people studying at the Medical faculty know more than students of the same year at faculties other than Medicine. Interesting results were obtained for a group of 3rd year students of first-cycle studies in Dietetics. They did not obtain a significantly better result in the knowledge test concerning the influence of diet and lifestyle on reproductive health. It would seem that one could expect at least a few highly knowledgeable students in a group of 3rd year students, but this was not confirmed by the study. In view of the obtained results, it was concluded that the Kohonen neural network is applicable to the analysis of data on the actual state of knowledge about the impact of lifestyle on reproductive health. (shrink)

Many studies confirm the fact that women do not have sufficient knowledge about reproductive health, which is a significant problem nowadays due to the large percentage of people who suffer from infertility. A sources of knowledge from which information about health, including reproductive health, is obtained have various levels of reliability. The aim of the study was to use regression trees to find which of the analysed parameters had the greatest impact on the level of respondents’ knowledge about fertility and (...) the impact of diet on fertility. The study was conducted among women who practice dance in Max Dance studio in Białystok. The group consisted of 42 women with an average age of 26.3 years, dancing in various dance styles at various levels of proficiency. A questionnaire on lifestyle and a sources of information on fertility was used; the questionnaire also contained a knowledge test focused on reproductive health and the impact of diet on fertility, in which the questions were based on information from the latest research. Three regression trees were created for three indicators determining the level of respondents’ knowledge. The obtained results revealed certain areas that have a significant impact on the level of knowledge about reproductive health, which may require additional education. The use of the regression trees method made it possible to determine the relationships between the analysed data that were not fully visible after standard biostatistical analyses had been performed. The created trees can be useful in improving the process of disseminating knowledge about reproductive health among women of childbearing age. (shrink)

The development of medicine is based on reliable medical research. This is a process that must be planned in detail and performed in accordance with the accepted study protocol, as any negligence – even a small one – or deviation from the protocol may result in distorted research results and – in consequence – to false conclusions. One of the key stages of research is the selection of the appropriate methodology, particularly in terms of tests that verify the posed hypotheses. (...) Each statistical method has a set of assumptions that have to be met in order for the method to be used. This paper explains why the appropriate selection of methods, verification of the required assumptions, and correct graphical representation of the obtained results are so important from the practical perspective. (shrink)