Volume 56 (2018): Issue 1 (December 2018)

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.

Hypertension is a common disease in highly industrialized societies, more often perceived as a health problem in adults rather than children. However, epidemiologists are currently paying more attention to the possibility of idiopathic hypertension during childhood. This article compares three classification models (logistic regression, classification trees and MARSplines) in order to determine the best classification model and distinguish the parameters that are most important in the detection of abnormal blood pressure in children. The study group consisted of 1,378 children aged between 7 and 18. After making comparisons between the methods, it was determined that MARSplines is the model that best assigns subjects to classes and can be an alternative in cases when traditional statistical methods cannot be used due to a lack of fulfillment of conditions. For prediction of abnormal blood pressure in this age group, the most important parameters were the heart rate and selected indicators of body proportions.

This study concerns the problem of late complications of antineo-plastic therapy. Reduced parameters of the cardiorespiratory system in childhood may have a tremendous impact on health. In order to assess the selected parameters, to evaluate physical endurance, and compare the results with those obtained for healthy children, a test was carried out on a treadmill, until 80% of maximum pulse rate was reached. To compare the differences between the treatment group and the control group, three approaches were used. The first one was the classical statistical inference, the second consisted in forming a multidimensional normal model and also involved modelling of the correlation between variables. The unstructured type of the working correlation matrix was chosen to obtain the results and correct standard errors. In the last approach, logistic regression was used to model the relationship between binary outcome and covariates, and to differentiate between the groups of patients on the basis of their cardiovascular parameters.

Parkinson’s Disease can be treated with the use of microelectrode recording and stimulation. This paper presents a data stream classifier that analyses raw data from micro-electrodes and decides whether the measurements were taken from the subthalamic nucleus (STN) or not. The novelty of the proposed approach is based on the fact that distances based on raw data are used. Two distances are investigated in this paper, i.e. Normalized Compression Distance (NCD) and Lempel-Ziv Jaccard Distance (LZJD). No new features needed to be extracted due to the fact that in the case of high-dimensional data the process is extremely time-consuming. The k-nearest neighbour (k-NN) was chosen as the classifier due to its simplicity, which is essential in data stream classification. Results obtained from classifiers based on k-NN: k-NN, k-NN were compared with Probabilistic Approximate Window (k-NN with PAW); k-NN with Probabilistic Approximate Window and Adaptive Windowing (k-NN with PAW and ADWIN); and Self Adjusting Memory k-NN (SAM k-NN), which use the proposed distances, with the performance of the same classifiers but using standard Euclidean distance. Prequential accuracy was chosen as the performance measure. The results of the experiments performed with the described approach are in most cases better, i.e. the performance measures for kNN classifiers that use NCD and LZJD distances are better by up to 8.5 per cent and 14 per cent, respectively. Moreover, the proposed approach performs better when compared with other stream classification algorithms, i.e. Hoeffding Tree, Naive Bayes, and Leveraging Bagging. In the discussed case, an improvement of classification rate of up to 17.9 per cent when using Lempel-Ziv Jaccard Distance instead of the Euclidean was noted.

The aim of the article is to present the application of the lean management method as appropriate for the management of the organizational system of psychiatric care in the Zealand region of Denmark. The organizational solutions of the Danish psychiatric care system presented in this paper are individualized and adapted to the regional needs of the residents. In Denmark, there are five administrative regions, in which each independently organizes its own system of medical (psychiatric) care. This means that the regions have considerable independence in choosing the acceptable and necessary methods of management, including – as is clear from the conducted research – the use of methods put-upon other areas of economy. Although the national laws in Denmark define certain conditions and guidelines for the functioning of psychiatric care (e.g. regarding the use of direct coercion/restrains for patients treated in the centres), there is a distinct separation of structures and methods of functioning throughout the whole country, which constitutes unique observation material – from the cognitive point of view. The authors of this paper conduct extensive research and analyse the systems of psychiatric care organizations in various countries (including Spain, Italy and Japan) and, as a result, the obtained results may lead to the selection of the best models from other systems (good organizational practices and management, the management methods in use), which can be applied in the currently reorganised system of the Polish psychiatric care. The choice of Denmark for the observational study is not accidental and is related not only to the fact that there is a large degree of systemic identity within the country and between the regions, but also because the country applies solutions addressed to patients with very different cultural conditions and needs, resulting from their descent, religion, and (world)-views. Denmark is one of those European countries that express a significant acceptance of diversity and tolerance, which is why communities with very different imponderables, denominations, and worldviews co-exist. In the area related to the organization of the psychiatric system, these conditions are of key importance. In the period from January 2015 to December 2017 the authors participated in study visits in Denmark, conducting research aimed at identifying the key success factors of the psychiatric care organization system in the country. The conducted analysis is also based on the analysis of literature and own and participant observations. The conclusions concerning this subject are also the result of interviews conducted with employees of the visited hospitals and system users, both professionals and patients. As the search for an optimal organizational model of psychiatric care is currently an ongoing concern in Poland, it seems justified to review the existing solutions in Europe and perform their critical analysis. A comparison of the adopted solutions was performed, in the context of, above all, the improvement of the quality of these services, their availability, and the satisfaction of patients and their families from the proposed organizational changes. The economic benefits of these solutions are also significant.

Even a small percentage of missing data can cause serious problems with analysis, reducing the statistical power of a study and leading to wrong conclusions being drawn. In the case of monitoring a woman’s monthly cycle, missing entries can appear even in a woman experienced in fertility awareness methods. Due to the fact that in a system of controlling a woman’s fertility, it is the most important to predict the day of ovulation and, ultimately, to determine the fertile window as much precisely as possible, much attention should be paid to the quality of the used data. This paper presents the results of handling missing observations as far as predicting the time during the cycle when a woman can become pregnant is concerned. Data taken from a multinational European study of daily fecundability was used to learn the quantitative part of the variety of a higher-order dynamic Bayesian network modeling a woman’s monthly cycle. The main goal of this paper is to examine whether omitting observations has an influence on the model’s reliability. The accuracy of comparison was examined based on two measures: the average percentage length of the infertile time during the monthly cycle and average percentage of days inside the fertile window classified as infertile.

The aim of this paper is to describe and assess the energetic-metabolic activity of selected muscles of upper and lower extremities during Rotational Training (RT). The influence of RT on temperature changes in the biceps and triceps brachii muscles as well as the quadriceps and biceps femoris muscles of healthy university students were verified, in addition to temperature differences between the left and right side before and after RT. The study was conducted on 18 subjects. RT was conducted in accordance with accepted forms of training methodology of collective fitness. An important part of RT was the performance of circular and rotational movements. Thermograms taken before and immediately after RT focused on 4 regions of selected agonists and synergists in the upper and lower body. The camera used was the infrared hand-held CEDIP Titanium 560M IR (USA), located at a distance of 10 m from the subject. After RT, median T_sk (skin temperature) decreased in almost all of the examined ROIs, except for the left and right Qf (the quadriceps femoris, rectus femoris, and sartorius muscles) as well as the left Tb (triceps brachii) in female subjects. In male subjects, left and right T_sk of Qf increased both for the left and right Tb. Left-Right ΔT_sk (temperature difference) was statistically significant (p <0.05) for Of, Bf, Bb, Tb in female as well as male subjects. It was concluded that thermography is a non-invasive, safe, and low-cost method for the recording of physiological response of the skin to RT.

Statistics is the science of collection, summarizing, presentation and interpretation of data. Moreover, it yields methods used in the verification of research hypotheses. The presence of a statistician in a research group remarkably improves both the quality of design and research and the optimization of financial resources. Moreover, the involvement of a statistician in a research team helps the physician to effectively utilize the time and energy spent on diagnosing, which is an important aspect in view of limited healthcare resources. Precise, properly designed and implemented Computerized Clinical Decision Support Systems certainly lead to the improvement of healthcare and the quality of medical services, which increases patient satisfaction and reduces financial burdens on healthcare systems.

The study investigates the possibility of applying texture analysis (TA) for testing Duchenne Muscular Dystrophy (DMD) therapies. The work is based on the Golden Retriever Muscular Dystrophy (GRMD) canine model, in which 3 phases of canine growth and/or dystrophy development are identified: the first phase (0–4 months of age), the second phase (from over 4 to 6 months), and the third phase (from over 6 months to death). Two differentiation problems are posed: (i) the first phase vs. the second phase and (ii) the second phase vs. the third phase. Textural features are derived from T2-weighted Magnetic Resonance Imaging (MRI) images. In total, 37 features provided by 8 different TA methods (statistical, filter-based, and model-based) have been tested. The work focuses on finding such textural features that evolve along with the dog’s growth. These features are indicated by means of statistical analyses and eliminated from further investigation, as they may disturb the correct assessment of response to treatment in dystrophy. The relative importance of each remaining feature is then assessed with the use of the Monte Carlo (MC) procedure. Furthermore, feature selection based on the MC procedure is employed to find the optimal subset of age-independent features. Finally, three classifiers are used for evaluating different sets of textural features: Adaptive Boosting (AB), back-propagation Neural Network (NN), and nonlinear Support Vector Machines (SVM). The best subsets of age-independent features ensure 80.0% and 78.5% of correctly identified phases of dystrophy progression, for the first (i) and second (ii) differentiation problem respectively.

The aim of the article is to present the results of bibliometric analyzes of scientific papers on the quality management of medical services published in 2001–2017 and indexed in the Scopus database. The analysis uses basic techniques of bibliometric analysis with the technical support of VOSviewer software. The publication proposes an original procedure for analyzing the literature on the subject. The results of the study allowed to determine the trends in the number of publications from 2010 to 2017. At the same time, an analysis of areas of science was presented, in which issues related to the management of the quality of medical services were analyzed, as well as citation of main authors and research centers. The whole analysis concerning the topic of quality management of medical services and bibliometric analysis of scientific works on the concepts and interrelations studied has identified the main six clusters that related to the management of quality of medical services ranging from broadly understood changes in healthcare organizations, internal quality management factors, development issues and education, regulation and standardization of the concept of quality improvement, and technological aspects of quality management in medical services. It seems, therefore, that the conducted studies can be considered as a specific guide for those interested in risk and uncertainty, despite the fact that they are not free of restrictions, for example, due to the narrowing of the time or criteria concerning the types of documents examined. In this context, the analyzes carried out give a wide range of opportunities to propose new research ideas on the above issues in contemporary organizations.

Public universities in Poland receive fairly limited financial support for creating e-textbooks (interactive online textbooks) and lack the appropriate ICT competences among teaching staff, especially in the case of non-technical universities. The authors propose a pedagogical and technological paradigm for e-textbooks in medical education using open source software with minimal IT skills required. Technologies used to develop e-textbooks are connected with: publication and distribution of e-textbooks, e-book readers, and editing tools. The paper also discusses a survey that targeted students of medical sciences, which focused on their understanding of their educational needs that can be met through new online resources as well as their expectations of how such e-textbooks should be like.

Textbooks have played the leading role in academic education for centuries and their form has evolved, adapting to the needs of students, teachers and technological possibilities. Advances in technology have caused educators to look for new sources of knowledge development, which students could use inside and outside the classroom. Today’s sophisticated learning tools range from virtual environments to interactive multimedia resources, which can be called e-textbooks. Different types of new educational materials that go beyond printed books are now used to support the academic curriculum, with the most interesting ones exemplified in this article to show their value in medical and life sciences education. Certain interesting attempts by Polish publishers at applying technology to support both self-paced and tutor-paced student learning in the medical profession and related areas are presented. The data was collected through a review of literature, discussions with e-learning specialists and medical students, as well as an analysis of examples of good practices. The article also discusses the results of a countrywide survey on the use of e-textbooks to enhance medical education. The research investigates the targeted academic staff’s attitudes towards the use of e-textbooks, the limitations of their implementation, and the character of e-resources currently used by Polish higher education medical institutions.

Resources of professional companies operating on the medical services market contain data from a huge number of transactional documents. This allows them to collect and process, among other actions, information about medical products. Organized data is obviously more valuable. In this paper, the possibility of supporting the process of organizing information is considered, with the goal to extract values of attributes of medical products from brief descriptions in transactional documents. This helps to build a structured product specification and makes it possible to make comparisons between products. For this purpose, an approach based on regular expressions and their generation with the use of the genetic algorithm is proposed. The results presented in the paper show a great potential of the presented method.

Coreference resolution is the task of finding all expressions that refer to the same entity in a text. It is one of the higher level NLP (Natural Language Processing) tasks. It allows, for example, to extract more information about medical products from larger texts. A product such as ‘ambidextrous gloves’ may appear in a text in many different forms. For example, they could be referred to by the pronoun ‘they’, such as in this sentence. The algorithm presented in this paper finds pronouns and for each of them (except the pleonastic ‘it’) it creates a coreference candidate with entities that appeared earlier in the same sentence or in the previous sentence. Each candidate (pair of mentions) is described by 48 binary features which represent their grammatical and location properties. In the training set, each pair is marked as a coreference or not, based on which a decision tree classifier is trained. A classifier with a high precision of 0.94 and a decent recall of 0.61 were obtained on the training set, still with a good precision out of a sample of 0.64.