Novel Nature Inspired Techniques in Medical Data Mining

AbstractIn this work we have studied, evaluated and proposed different swarm intelligence techniques for mining information from loosely structured medical textual records with no a priori knowledge (a large dataset). The output of this task is a set of ordered/nominal attributes suitable for rule discovery mining.Information mining from textual data becomes a very challenging task when the structure of the text record is loose without any rules. The task becomes even harder when natural language is used and no a priori knowledge is available.First, classical approaches such as basic statistic approaches, single and multiple word frequency analysis, etc., have been used to simplify the textual data and provide an overview of the data. Finally, an ant-inspired self-learning approach has been used to automatically provide a simplified dominant structure, presenting structure of the records in the human readable form that can be further utilized in the mining process as it describes the vast majority of the records.Note that this project is an ongoing process (and research) and new data are irregularly received from the medical facility, justifying the need for robust and fool-proof algorithms

Application of Internet of Things in Health Care

The paper focuses on the continuously growing area of Internet of Things and its application to health care. We discuss several important aspects, namely quality, and relevance of data acquired. We illustrate IoT by a case study of diabetes mellitus personalised treatment. Modern type 1 diabetes mellitus therapy is now unimaginable without intensive glycaemia monitoring. In the last decade the possibility of real time continuous glucose monitoring (RT-CGMS) was realised along with integration to some types of insulin pump. Currently the research focuses on continuous glucose monitoring systems that have following advantages: non-invasiveness, high customer acceptance; comfort in use; ease in use; accuracy; long-term measurement up to 4 weeks; calibrating unit integrated; alerts for low or highs of glucose level; enabling higher lifestyle flexibility, e.g. physical activity, food, medication; wireless data and energy transmission; infection risk is minimised. Obviously several sensors are necessary to acquire the contextual data, in particular vital parameters, physical activity, and stress. All measured data must be collected and evaluated in parallel. The aim is to identify the mutual relations in measured parameters, the differences among patients and finally the most important parameters for development of personalised data models

Making Meaning Together: An Autoethnography Study On Our Role In Ethics Education

Representation of diverse people’s perspectives, cultures, and ideas enriches societies. Equally important for communities to flourish is to have diverse perspectives on what good ethics education is. For 50 years the European Society of Engineering Education (SEFI) has been uniting and supporting engineering educators and researchers from around the globe and particularly from Europe. However, involvement from institutions in Eastern Europe is still very low. To diversify and strengthen the community by bringing perspectives from these countries, we engaged in an autoethnography study to share insights on participation barriers broadly and ethics education, more specifically. We choose autoethnography as this methodology allows researchers not only to share their own experiences but to connect in making meaning of a phenomena and to form a community of practice. The researchers and authors of this paper are representing STEM institutions in three Eastern European countries. Applying an interactionist approach, we engaged in a community of practice group to discuss the current state of the art of ethics education in our own institutions and to talk about the experiences with ethics education, academic integrity, and ethics culture. We collectively selected an appropriate framework and applied that framework to interpret the findings. Transcripts were analysed by all five researchers. The paper and the presentation will be presented together as a narrative story. The goal of this work is to form a community of practice and to create an agenda to engage the newly formed community of practice with the broader SEFI ethics education community

Perspectives on the COVID-19 Vaccination Rollout in 17 Countries:Reflexive Thematic and Frequency Analysis Based on the Strengths, Weaknesses, Opportunities, and Threats (SWOT) Framework

BACKGROUND: As the SARS-CoV-2 virus created a global pandemic and rapidly became an imminent threat to the health and lives of people worldwide, the need for a vaccine and its quick distribution among the population was evident. Due to the urgency, and on the back of international collaboration, vaccines were developed rapidly. However, vaccination rollouts showed different success rates in different countries and some also led to increased vaccine hesitancy.OBJECTIVE: The aim of this study was to identify the role of information sharing and context sensitivity in various vaccination programs throughout the initial COVID-19 vaccination rollout in different countries. Moreover, we aimed to identify factors in national vaccination programs related to COVID-19 vaccine hesitancy, safety, and effectiveness. Toward this end, multidisciplinary and multinational opinions from members of the Navigating Knowledge Landscape (NKL) network were analyzed.METHODS: From May to July 2021, 25 completed questionnaires from 27 NKL network members were collected. These contributors were from 17 different countries. The responses reflected the contributors' subjective viewpoints on the status and details of the COVID-19 vaccination rollout in their countries. Contributors were asked to identify strengths, weaknesses, opportunities, and threats (ie, SWOT) of the respective vaccination programs. The responses were analyzed using reflexive thematic analysis, followed by frequency analysis of identified themes according to the represented countries.RESULTS: The perspectives of NKL network members showed a link between organizational elements of the vaccination rollout and the accompanying societal response, both of which were related to strengths and weaknesses of the process. External sociocultural variables, improved public communication around vaccination-related issues, ethical controversies, and the spread of disinformation were the dominant themes related to opportunities and challenges. In the SWOT 2×2 matrix, Availability and Barriers emerged as internal categories, whereas Transparent communication and promotion and Societal divide emerged as key external categories.CONCLUSIONS: Inventory of themes and categories inspired by elements of the SWOT framework provides an informative multidisciplinary perspective for effective implementation of public health strategies in the battle against COVID-19 or any future pandemics of a similar nature.</p

Report on SHAFE policies, strategies and funding

The objective of Working Group (WG) 4 of the COST Action NET4Age-Friendly is to examine existing policies, advocacy, and funding opportunities and to build up relations with policy makers and funding organisations. Also, to synthesize and improve existing knowledge and models to develop from effective business and evaluation models, as well as to guarantee quality and education, proper dissemination and ensure the future of the Action. The Working Group further aims to enable capacity building to improve interdisciplinary participation, to promote knowledge exchange and to foster a cross-European interdisciplinary research capacity, to improve cooperation and co-creation with cross-sectors stakeholders and to introduce and educate students SHAFE implementation and sustainability (CB01, CB03, CB04, CB05). To enable the achievement of the objectives of Working Group 4, the Leader of the Working Group, the Chair and Vice-Chair, in close cooperation with the Science Communication Coordinator, developed a template (see annex 1) to map the current state of SHAFE policies, funding opportunities and networking in the COST member countries of the Action. On invitation, the Working Group lead received contributions from 37 countries, in a total of 85 Action members. The contributions provide an overview of the diversity of SHAFE policies and opportunities in Europe and beyond. These were not edited or revised and are a result of the main areas of expertise and knowledge of the contributors; thus, gaps in areas or content are possible and these shall be further explored in the following works and reports of this WG. But this preliminary mapping is of huge importance to proceed with the WG activities. In the following chapters, an introduction on the need of SHAFE policies is presented, followed by a summary of the main approaches to be pursued for the next period of work. The deliverable finishes with the opportunities of capacity building, networking and funding that will be relevant to undertake within the frame of Working Group 4 and the total COST Action. The total of country contributions is presented in the annex of this deliverable

Artificial Intelligence and Women Researchers in the Czech Republic

Artificial intelligence as a research area has been continuously growing for several decades. Many applications were developed in various domains. Medicine and health care have attracted more intensive attention thanks to rapid technological development that has accelerated generation of large volumes of data requiring intelligent analysis and evaluation. This article illustrates, through examples of women researchers and selected AI projects in medicine, the wide spectrum of applications developed during the last fifteen years in the Czech Republic, and in particular at the Czech Technical University in Prague. Women researchers played an important and irreplaceable role since the advent of AI research in the Czech Republic. By their example, they motivated many young female students to join the community and start their research career in the AI area. They frequently participated in research projects led by the senior women researchers. The presented overview of projects illustrates the diversity of the medical area and the potential of AI methods that can be used for solving data- and knowledge-intensive problems. We briefly touch on the AI study programs. In conclusion, we point out the future challenges in AI and its applications in medicine and health care

Utilization Possibilities of Multi-Agent Systems in Medicine

The aim of the paper is to inform about existing medical applications of multiagent systems at foreign institutions and about the system for monitoring and diagnostics under development at the Gerstner Laboratory, Czech Technical University in Prague, Faculty of Electrical Engineering. We present a knowledge-based model of agents’ mutual awareness (social knowledge). The tri-base acquaintance (3bA) model formalizing agent’s social behaviour knowledge and agent’s cooperation neighbourhood knowledge is enhanced to support attention focussing and to ensure a holistic complex perception of the problem

Artificial Intelligence and Women Researchers in the Czech Republic

Artificial intelligence as a research area has been continuously growing for several decades. Many applications were developed in various domains. Medicine and health care have attracted more intensive attention thanks to rapid technological development that has accelerated generation of large volumes of data requiring intelligent analysis and evaluation. This article illustrates, through examples of women researchers and selected AI projects in medicine, the wide spectrum of applications developed during the last fifteen years in the Czech Republic, and in particular at the Czech Technical University in Prague. Women researchers played an important and irreplaceable role since the advent of AI research in the Czech Republic. By their example, they motivated many young female students to join the community and start their research career in the AI area. They frequently participated in research projects led by the senior women researchers. The presented overview of projects illustrates the diversity of the medical area and the potential of AI methods that can be used for solving data- and knowledge-intensive problems. We briefly touch on the AI study programs. In conclusion, we point out the future challenges in AI and its applications in medicine and health care