Volume 47 (2016): Issue 1 (December 2016)

Infertility is currently a common problem with causes that are often unexplained, which complicates treatment. In many cases, the use of ART methods provides the only possibility of getting pregnant. Analysis of this type of data is very complex. More and more often, data mining methods or artificial intelligence techniques are appropriate for solving such problems. In this study, classification trees were used for analysis. This resulted in obtaining a group of patients characterized most likely to get pregnant while using in vitro fertilization.

This paper reports on a multiresolution analysis of EEG signals. The dominant frequency components of signals with and without observed epileptic discharges were compared. The study showed that there were significant differences in dominant frequency between the signals with epileptic discharges and the signals without discharges. This gives the ability to identify epilepsy during EEG examination. The frequency of the signals coming from the frontal, central, parietal and occipital channels are similar. Multiresolution analysis can be used to describe the activity of brain waves and to try to predict epileptic seizures, thereby contributing to precise medical diagnoses.

There are high hopes for using the artificial neural networks (ANN) technique to predict results of infertility treatment using the in vitro fertilization (IVF) method. Some reports show superiority of the ANN approach over conventional methods. However, fully satisfactory results have not yet been achieved. Hence, there is a need to continue searching for new data describing the treatment process, as well as for new methods of extracting information from these data. There are also some reports that the use of principal component analysis (PCA) before the process of training the neural network can further improve the efficiency of generated models. The aim of the study herein presented was to verify the thesis that the use of PCA increases the effectiveness of the prediction by ANN for the analysis of results of IVF treatment. Results for the PCA-ANN approach proved to be slightly better than the ANN approach, however the obtained differences were not statistically significant.

Biological time series have a finite number of samples with noise included in them. Because of this fact, it is not possible to reconstruct phase space in an ideal manner. One kind of biomedical signals are electrohisterographical (EHG) datasets, which represent uterine muscle contractile activity. In the process of phase space reconstruction, the most important thing is suitable choice of the method for calculating the time delay τ and embedding dimension d, which will reliably reconstruct the original signal. The parameters used in digital signal processing are key to arranging adequate parameters of the analysed attractor embedded in the phase space. The aim of this paper is to present a method employed for phase space reconstruction for EHG signals that will make it possible for their further analysis to be carried out.

As defined by the National Institutes of Health: “Biomedical engineering integrates physical, chemical, mathematical, and computational sciences and engineering principles to study biology, medicine, behavior, and health”. Many issues in this area are closely related to fluid dynamics. This paper provides an overview of the basic concepts concerning Computational Fluid Dynamics and its applications in medicine.

The aim of the study presented in this article is to show correspondence analysis as a method useful in the diagnosis of coexistence of category variables in antecedents of innovativeness, with the positions of the respondents representing various medical professions in hospitals. Primary data obtained in the course of empirical research, carried out using a questionnaire study on a sample of 459 respondents representing 8 public hospitals in Poland, is used to this aim. To follow up on the achievements of the analysis, literature on the issue of innovativeness and its antecedents was also used. The results of the correspondence analysis allows one to confirm the thesis of the different opinions of doctors, nurses/midwives and managers regarding the level of significance of antecedents of innovativeness, where for doctors and managers in this context the most important is financial optimization, and for nurses the improvement of the quality of medical services. The results may provide an important clue to the chief executives of hospitals in the context of further changes and innovativeness necessary to achieve the desired efficiency of these organizations.

Analysis of Electroencephalography (EEG) signals has recently awoken the increased interest of numerous researchers all around the world with regard to rapid development of Brain-Computer Interaction-related research areas and because EEG signals are implemented in most of the non-invasive BCI systems, as they provide necessary information regarding activity of the brain. In this paper, a very early stage pilot study on implementation of filtering based on fractional-order calculus (Bi-Fractional Filters – BFF) for the purpose of EEG signal classification is presented in brief.

Nutrition is one of the most important environmental factors affecting the physical development and health of children. Education in this area and the development of proper eating habits are priorities. A prerequisite for the proper nutrition of preschool children is knowledge of proper nutrition of people working there. The aim of this study was an evaluation of the knowledge of kindergarten employees participating in the course “Diet full of life – courses in the field of children’s nutrition”. The study included 90 employees of nurseries and kindergartens, participants of the course in the field of children’s nutrition. The research tool was an original questionnaire. Study I (pre-test) was performed before the beginning of the course, while study II (post-test) was performed after its completion. Generalized Linear Models with a Generalized Estimating Equations extension was used to estimate the impact of the number of covariates on knowledge of course participants, taking into consideration the correlation between before- and after-course results. An increase in the knowledge of the participants of the investigated course on children’s nutritional standards was significant and reached 2.053 points on average. No relationship between age, job position, and knowledge level was determined. In the area of principles of proper nutrition for children, older participants had a lower level of knowledge compared to younger ones, and participants with higher education showed a significantly higher knowledge increase as compared to those with vocational education. A significant knowledge increase in the field of dietary behaviors of children was obtained during the course by all examined women, 1.6 points on average (p < 0.001). Younger participants obtained significantly more knowledge from the course than older ones (p < 0.001). Thus, it can be concluded that realization of the course entitled “Diet full of life” specifically relating to young children’s nutrition affected a significant increase in participant knowledge, particularly among the younger age groups and people with higher education. Kindergarten employees need constant supplemental education in the form of training courses, during which they acquire actual knowledge given in an accessible manner for use in practice. The proper assessment of the supplemental education course presented herein, as well as of the course participants, was performed using General Estimating Equations.

Distance education undoubtedly has many advantages, such as individualization of the learning process, unified transmission of teaching materials, the opportunity to study at any place and any time, reduction of financial costs for commuting to classes or accommodation of participants, etc. Adequate working conditions on the e-learning portal must also be present, eg. well-prepared, substantive courses and good communication between the participants. Therefore, an important element in the process of conducting e-learning courses is to measure the increase of knowledge and satisfaction of participants with distance learning. It allows for fine-tuning the content of the course and for classes to be properly organized. This paper presents the results of teaching and assessment of satisfaction with e-learning courses in “Problems of multiculturalism in medicine”, “Selected issues of visual rehabilitation” and “Ophthalmology and Ophthalmic Nursing”, which were carried out experimentally at the Faculty of Health Sciences at the Medical University of Bialystok for nursing students for the 2010/2011 academic year. The study group consisted of 72 part-time students who learnt in e-learning mode and the control group of 87 students who learnt in the traditional way. The students’ opinions about the teaching process and final exam scores were analyzed based on a specially prepared survey questionnaire. Organization of e-learning classes was rated positively by 90% of students. The average result on the final exams for all distance learning subjects was at the level of 82%, while for classes taught in the traditional form it was 81%. Based on these results, we conclude that distance learning is as effective as learning according to the traditional form in medical education studies.