10.24105/ejbi.2018.14.2.7 OR Decision support systems Present and future
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Health care is a data-sensitive and data-rich industry. Designers of health administration curricula recognize that future health care providers and managers must be trained to use available analytical and database information technology (IT) to transform these data into information helpful to the decision-maker. However, as the data available to administrators and clinicians proliferates, additional skills are needed to select data that is pertinent and useful. This paper presents the results of the collaboration of partners from Bohemia and University of Nevada and focuses on three areas: threats to the effective use of data to support health care decision-making;. health care decision support research and training strategies; future cross-disciplinary collaboration in health care decision support. Advanced IT methods have the potential to assist clinical and managerial decision-making. If further discussion is stimulated about the introduction of advanced IT methods into the health care management curriculum and research agenda, this paper will achieve its goal.
Space and time are fundamental attributes of the external world. Deciphering the brain mechanisms involved in processing the surrounding environment is one of the main challenges in neuroscience. This is particularly defiant when situations change rapidly over time because of the intertwining of spatial and temporal information. However, understanding the cognitive processes that allow coping with dynamic environments is critical, as the nervous system evolved in them due to the pressure for survival. Recent experiments have revealed a new cognitive mechanism called time compaction. According to it, a dynamic situation is represented internally by a static map of the future interactions between the perceived elements (including the subject itself). The salience of predicted interactions (e.g. collisions) over other spatiotemporal and dynamic attributes during the processing of time-changing situations has been shown in humans, rats, and bats. Motivated by this ubiquity, we study an artificial neural network to explore its minimal conditions necessary to represent a dynamic stimulus through the future interactions present in it. We show that, under general and simple conditions, the neural activity linked to the predicted interactions emerges to encode the perceived dynamic stimulus. Our results show that this encoding improves learning, memorization and decision making when dealing with stimuli with impending interactions compared to no-interaction stimuli. These findings are in agreement with theoretical and experimental results that have supported time compaction as a novel and ubiquitous cognitive process.
- Klíčová slova
- Neural networks, dynamic environments, interactions, learning, memory, spatiotemporal cognition,
- MeSH
- lidé MeSH
- modely neurologické * MeSH
- mozek * fyziologie MeSH
- neuronové sítě * MeSH
- rozhodování fyziologie MeSH
- učení fyziologie MeSH
- vnímání času * fyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
The purpose of this paper is to present the development of a qualitative approach to environmental risk assessment (QAERA) in transport. The approach is described as a model developed for the future software tool which will be utilizable as a risk decision support system. The basic part is aimed on developing a quantitative environmental risk assessment. Thus, this paper describes a set of 6 pillars of safety and security. Accordingly, the paper contains both chosen safety and security indicators and selected criteria for assessing the risk of launching the environmental change of global model thinking in the transport sector. The environmental risk assessment as a global model of thinking was originally based on historical experience but, nowadays, it is changing. Based on new expert knowledge, more precisely, on input of new global data, paper displays an environmental risk assessment with actual interpretation. The discussion of the paper is oriented to support research results, a new knowledge-oriented approach to global climate changes, using suitable risk assessment methods and technics. The result of the paper is a new approach for the modeling of environmental risk assessment in the transport sector.
- Klíčová slova
- common safety method, decision support system, environment, expert evaluation, risk assessment, transport sector,
- MeSH
- doprava * MeSH
- hodnocení rizik MeSH
- klimatické změny * MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: The harm reduction (HR) approach to injecting drug use was rapidly adopted in Central Europe following the fall of the Iron Curtain. The associated social and economic transformation had significant consequences for drug policies in the region. A large number of emerging services have been dependent on funding from a wide range of national and/or local funding programmes, which continue to be unstable, and closely associated with political decisions and insufficient institution building. A sharp distinction is made between health and social services, often without regard to client input. The main objective of the paper is to identify the causes of the funding problems currently faced by HR services in the context of their history of institution building which represents a major threat to the future of HR services in the region. METHODS: Qualitative content analysis of documents was conducted in the development of two case studies of the Czech and Slovak Republics. The body of documentation under study comprised policy documents, including National Drug Strategies, Action Plans, ministerial documents, and official budgets and financial schedules, as well as documents from the grey literature and expert opinions. RESULTS: The insufficient investments in finalising the process of the institution building of HR services have resulted in a direct threat to their sustainability. An unbalanced inclination to the institutionalisation of HR within the domain of social services has led to a misperception of their integrity, as well as to their funding and long-term sustainability being endangered. In addition, this tendency has had a negative impact on the process of the institutionalisation of HR within the system of healthcare. CONCLUSION: The case study revealed a lack of systemic grounding of HR services as interdisciplinary health-social services. The aftermath of the financial crisis in 2008 fully revealed the limitations of the funding system established ad hoc in the 1990s, which remains present until today, together with all its weak points. The entire situation is responsible for the dangerous erosion of the interpretation of the concept of harm reduction, which is supported by various stereotypes and false, or ideological, interpretations of the concept.
- Klíčová slova
- Case studies, Comparative qualitative analysis, Czech Republic, Drug policy, Financial support, Harm reduction, Slovak Republic, System analysis,
- MeSH
- lidé MeSH
- poruchy spojené s užíváním psychoaktivních látek * MeSH
- poskytování zdravotní péče MeSH
- snížení rizika poškození * MeSH
- veřejná politika MeSH
- zdravotnické služby MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Present and future climatic trends are expected to markedly alter water fluxes and stores in the hydrologic cycle. In addition, water demand continues to grow due to increased human use and a growing population. Sustainably managing water resources requires a thorough understanding of water storage and flow in natural, agricultural, and urban ecosystems. Measurements of stable isotopes of water (hydrogen and oxygen) in the water cycle (atmosphere, soils, plants, surface water, and groundwater) can provide information on the transport pathways, sourcing, dynamics, ages, and storage pools of water that is difficult to obtain with other techniques. However, the potential of these techniques for practical questions has not been fully exploited yet. Here, we outline the benefits and limitations of potential applications of stable isotope methods useful to water managers, farmers, and other stakeholders. We also describe several case studies demonstrating how stable isotopes of water can support water management decision-making. Finally, we propose a workflow that guides users through a sequence of decisions required to apply stable isotope methods to examples of water management issues. We call for ongoing dialogue and a stronger connection between water management stakeholders and water stable isotope practitioners to identify the most pressing issues and develop best-practice guidelines to apply these techniques.
- Klíčová slova
- Agricultural management, Climate change, Forest management, Stable isotopes of water, Stakeholders, Water resources management,
- MeSH
- ekosystém * MeSH
- izotopy analýza MeSH
- lesy * MeSH
- ochrana vodních zdrojů metody MeSH
- podzemní voda chemie MeSH
- vodní zdroje MeSH
- zemědělství * metody MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
- Názvy látek
- izotopy MeSH
This paper presents an adaptive system intended to address workload imbalances between pilots in future flight decks. Team performance can be maximized when task demands are balanced within crew capabilities and resources. Good communication skills enable teams to adapt to changes in workload, and include the balancing of workload between team members This work addresses human factors priorities in the aviation domain with the goal to develop concepts that balance operator workload, support future operator roles and responsibilities, and support new task requirements, while allowing operators to focus on the most safety critical tasks. A traditional closed-loop adaptive system includes the decision logic to turn automated adaptations on and off. This work takes a novel approach of replacing the decision logic, normally performed by the automation, with human decisions. The Crew Workload Manager (CWLM) was developed to objectively display the workload between pilots and recommend task sharing; it is then the pilots who "close the loop" by deciding how to best mitigate unbalanced workload. The workload was manipulated by the Shared Aviation Task Battery (SAT-B), which was developed to provide opportunities for pilots to mitigate imbalances in workload between crew members. Participants were put in situations of high and low workload (i.e., workload was manipulated as opposed to being measured), the workload was then displayed to pilots, and pilots were allowed to decide how to mitigate the situation. An evaluation was performed that utilized the SAT-B to manipulate workload and create workload imbalances. Overall, the CWLM reduced the time spent in unbalanced workload and improved the crew coordination in task sharing while not negatively impacting concurrent task performance. Balancing workload has the potential to improve crew resource management and task performance over time, and reduce errors and fatigue. Paired with a real-time workload measurement system, the CWLM could help teams manage their own task load distribution.
- Klíčová slova
- adaptive human-automation systems, cognitive state assessment, crew resource management, human-computer interaction, neuroergonomics, teamwork,
- Publikační typ
- časopisecké články MeSH
Artificial Intelligence (AI) has evolved significantly over the past decades, from its early concepts in the 1950s to the present era of deep learning and natural language processing. Advanced large language models (LLMs), such as Chatbot Generative Pre-Trained Transformer (ChatGPT) is trained to generate human-like text responses. This technology has the potential to revolutionize various aspects of gastroenterology, including diagnosis, treatment, education, and decision-making support. The benefits of using LLMs in gastroenterology could include accelerating diagnosis and treatment, providing personalized care, enhancing education and training, assisting in decision-making, and improving communication with patients. However, drawbacks and challenges such as limited AI capability, training on possibly biased data, data errors, security and privacy concerns, and implementation costs must be addressed to ensure the responsible and effective use of this technology. The future of LLMs in gastroenterology relies on the ability to process and analyse large amounts of data, identify patterns, and summarize information and thus assist physicians in creating personalized treatment plans. As AI advances, LLMs will become more accurate and efficient, allowing for faster diagnosis and treatment of gastroenterological conditions. Ensuring effective collaboration between AI developers, healthcare professionals, and regulatory bodies is essential for the responsible and effective use of this technology. By finding the right balance between AI and human expertise and addressing the limitations and risks associated with its use, LLMs can play an increasingly significant role in gastroenterology, contributing to better patient care and supporting doctors in their work.
- Klíčová slova
- artificial intelligence, gastroenterology, large language model,
- MeSH
- deep learning MeSH
- gastroenterologie * MeSH
- lidé MeSH
- umělá inteligence * MeSH
- zpracování přirozeného jazyka * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
We live in a world characterized by biodiversity loss and global environmental change. The extinction of large carnivores can have ramifying effects on ecosystems like an uncontrolled increase in wild herbivores, which in turn can have knock-on impacts on vegetation regeneration and communities. Cheetahs (Acinonyx jubatus) serve important ecosystem functions as apex predators; yet, they are quickly heading towards an uncertain future. Threatened by habitat loss, human-wildlife conflict and illegal trafficking, there are only approximately 7100 individuals remaining in nature. We present the most comprehensive genome-wide analysis of cheetah phylogeography and conservation genomics to date, assembling samples from nearly the entire current and past species' range. We show that their phylogeography is more complex than previously thought, and that East African cheetahs (A. j. raineyi) are genetically distinct from Southern African individuals (A. j. jubatus), warranting their recognition as a distinct subspecies. We found strong genetic differentiation between all classically recognized subspecies, thus refuting earlier findings that cheetahs show only little differentiation. The strongest differentiation was observed between the Asiatic and all the African subspecies. We detected high inbreeding in the Critically Endangered Iranian (A. j. venaticus) and North-western (A. j. hecki) subspecies, and show that overall cheetahs, along with snow leopards, have the lowest genome-wide heterozygosity of all the big cats. This further emphasizes the cheetah's perilous conservation status. Our results provide novel and important information on cheetah phylogeography that can support evidence-based conservation policy decisions to help protect this species. This is especially relevant in light of ongoing and proposed translocations across subspecies boundaries, and the increasing threats of illegal trafficking.
- Klíčová slova
- Acinonyx jubatus, cheetah, conservation genomics, double-digest restriction site associated DNA (ddRAD) sequencing, phylogeography,
- MeSH
- Acinonyx * genetika MeSH
- ekosystém MeSH
- genom MeSH
- genomika MeSH
- lidé MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Írán MeSH
Digital transformation is widely understood as a process where technology is used to modify an organization's products and services and to create new ones. It is rapidly advancing in all sectors of society. Researchers have shown that it is a multidimensional process determined by human decisions based on ideologies, ideas, beliefs, goals, and the ways in which technology is used. In health care and health, the end result of digital transformation is digital health. In this study, a detailed literature review covering 560 research articles published in major journals was performed, followed by an analysis of ideas, beliefs, and goals guiding digital transformation and their possible consequences for privacy, human rights, dignity, and autonomy in health care and health. Results of literature analyses demonstrated that from the point of view of privacy, dignity, and human rights, the current laws, regulations, and system architectures have major weaknesses. One possible model of digital health is based on the dominant ideas and goals of the business world related to the digital economy and neoliberalism, including privatization of health care services, monetization and commodification of health data, and personal responsibility for health. These ideas represent meaningful risks to human rights, privacy, dignity, and autonomy. In this paper, we present an alternative solution for digital health called human-centric digital health (HCDH). Using system thinking and system modeling methods, we developed a system model for HCDH. It uses 5 views (ideas, health data, principles, regulation, and organizational and technical innovations) to align with human rights and values and support dignity, privacy, and autonomy. To make HCDH future proof, extensions to human rights, the adoption of the principle of restricted informational ownership of health data, and the development of new duties, responsibilities, and laws are needed. Finally, we developed a system-oriented, architecture-centric, ontology-based, and policy-driven approach to represent and manage HCDH ecosystems.
- Klíčová slova
- artificial intelligence, autonomy, digital economy, digital health, dignity, human rights, modeling, neoliberalism, privacy, system analysis,
- MeSH
- digitální technologie MeSH
- digitální zdraví * MeSH
- lidé MeSH
- lidská práva MeSH
- péče orientovaná na pacienta * MeSH
- soukromí MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
This study presents a comprehensive analytical framework for modeling electric vehicle (EV) charging infrastructures through a stochastic queueing-theoretic approach that explicitly incorporates critical customer behavioral dynamics. The proposed model addresses key phenomena often overlooked in classical frameworks, including customer impatience (reneging), balking behavior, feedback mechanisms, and state-dependent service threshold policies, within a finite-population, multiple-server environment. These behavioral elements reflect realistic operational scenarios in which users may opt not to join extended queues, abandon the system due to excessive delays, or return for service completion based on prior dissatisfaction. The system dynamics are formulated using a continuous-time Markov chain (CTMC), and the corresponding Chapman-Kolmogorov differential equations are derived to characterize state transitions. Employing a matrix-analytic solution technique, the steady-state probability distribution is obtained, enabling the computation of multiple performance metrics such as system occupancy, server utilization, abandonment rates, and throughput. Numerical simulations validate the model's applicability and highlight intricate interdependencies among customer tolerance thresholds, service quality levels, and operational performance indicators. The findings offer valuable insights into capacity planning, congestion control, and service optimization, providing a rigorous decision-support framework for the design and management of EV charging networks under uncertain and dynamic user behavior. The study also outlines practical managerial implications and suggests directions for future research to enhance the adaptability and efficiency of smart charging infrastructures.
