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An enormous number of magnetic resonance imaging (MRI) brain images were produced in hospitals and several MRI centers. To exploit the diagnosis in MRI brain image, “content-based image retrieval (CBIR)” system is accessed in the MRI brain image database. In this paper, a content-based MRI brain image retrieval system is presented, which is helpful in the medical field to seek a diagnosis in an MRI brain image that is similar to the example given. This paper consists of preprocessing, feature extraction, feature selection, similarity measure, and classification. In the preprocessing phase, the Wiener filter is used to remove the unwanted pixels from an MRI brain image. In the second phase, the features related to MRI brain image are extracted using characteristics of shape, margin, and density of the MRI. In the third stage, the features of MRI brain image were reduced using principal component analysis. CBIR classification is used in this method to gain effectual results. In the first stage, retrieval images are obtained using similarity measures using the similarity between the query image features and the derived trained image features. Finally, the classification stage is an extreme learning machine with probabilistic scaling used to classify the obtained retrieval output image and the query image. The result demonstrates that the proposed CBIR approach is robust and effectual compared with other latest work.

Objectives Optimization of Brain-Computer Interface by detecting the minimal number of morphological features of signal that maximize accuracy. Methods System of signal processing and morphological features extractor was designed, then the genetic algorithm was used to select such characteristics that maximize the accuracy of the signal’s frequency recognition in offline Brain-Computer Interface (BCI). Results The designed system provides higher accuracy results than a previously developed system that uses the same preprocessing methods, however, different results were achieved for various subjects. Conclusions It is possible to enhance the previously developed BCI by combining it with morphological features extraction, however, it’s performance is dependent on subject variability.

Objectives Disorders of consciousness are very big medical and social problem. Their variability, problems in precise definition and proper diagnosis make difficult assessing their causes and effectiveness of the therapy. In the paper we present our point of view to a problem of consciousness and its most common disorders. Methods For this moment scientists do not know exactly, if these disorders can be a result of simple but general mechanism, or a complex set of mechanisms, both on neural, molecular or system level. Presented in the paper simulations using neural network models, including biologically relevant consciousness’ modelling, help assess influence of specified causes. Results Nonmotoric brain activity can play important role within diagnostic process as a supplementary method for motor capabilities. Simple brain sensory (e.g. visual) processing of both healthy subject and people with consciousness disorders help checking hypotheses in the area of consciousness’ disorders’ mechanisms, including associations between consciousness and its neural correlates. Conclusions The results are promising. Project announced herein will be developed and its next result will be presented in subsequent articles.

The publication presents the “Okopaczaj” application which is aimed to promote health by increasing the awareness about the structure and the consequences of the diseases of the eyesight organ. The first part of the article focuses on the factors which affected creating the application and its general construction. The second part describes the tools of Godot, Blender and Photoshop which were used in the process of creating particular parts of the application. The third part presents the modes that are available in the “Okopaczaj” application as well as their functioning and available functions. The last part summarizes the article and the results of the research conducted with the use of the application.

Curriculum mapping is the process of designing a multidimensional model of an educational programme for a complete, more transparent and better-integrated learning experience. Many universities worldwide are building or expanding their technical infrastructure to manage their curricula. Our aim was to deliver a synopsis of current practices and describe the focus of research interest in implementing curriculum mapping tools for medical education. As part of the Building Curriculum Infrastructure in Medical Education (BCIME) project, we conducted a state-of-the-art narrative review of the literature. A systematised search of the PubMed/MEDLINE database for the years 2013–2019 resulted in 352 abstracts, from which 23 full-text papers were included in the final review. From these, we extracted guidance on 12 key characteristics of curriculum mapping tools. The collected experiences formed four thematic categories: visualisations, text descriptions and analysis, the outcome-based approach and adaptability in curriculum mapping. As result of the review, we summarised topics regarding ways of: implementating new competency-based catalogues (like NKLM) in curriculum mapping software (e. g., using dynamic checklists), methods of streamlining the authoring process (e. g., by automatic detection and alignment of action verbs in learning objectives descriptions) and graphical forms of presenting curriculum data (e. g., network visualisations using automatic clustering of related parts of a curriculum based on similarities between textual descriptions). We expect further developments in text-mining methods and visual/learning analytics in curriculum mapping. The collected data informed the design of a new curriculum management system called EduPortfolio, which is currently being implemented by the BCIME project.

The experience of the ongoing pandemic gives rise to a variety of questions, touching – among others – upon its biological aspects. Among the most often raised issues is why the situation has deteriorated to such a degree in the Mediterranean basin and the American eastern seaboard. This work identifies possible links between the protein folding process and the aforementioned epidemic. Given the circumstances, it should be regarded as a popular science article.