Intelligent machines have reached capabilities that go beyond a level human being can fully comprehend without sufficiently detailed understanding of the underlying mechanisms. The choice moves in game Go (generated by Deep Mind?s Alpha Zero [1]) are an impressive example artificial intelligence system calculating results even expert for hardly retrace [2]. But this is, quite literally, toy example. In reality, intelligent algorithms encroaching more and into our everyday lives, be it...

Individual traffic significantly contributes to climate change and environmental degradation. Therefore, innovation in sustainable mobility is gaining importance as it helps reduce pollution. However, effects of new ideas are difficult estimate advance strongly depend on the individual participants. The application agent technology particularly promising focuses modelling heterogeneous preferences behaviours. In this paper, we show how agent-based models suitable address three pressing...

The initiation of sodium–glucose cotransporter 2 (SGLT2) inhibitor treatment was shown to reduce pulmonary artery pressure (PAP) in New York Heart Association (NYHA) class III heart failure (HF) patients with an implanted PAP sensor. We aimed investigate the impact SGLT2-I on vascular resistance (PVR), capillary wedge (PCWP), arterial capacitance (PAC), and right ventricle (RV) PA (RV-PA) coupling a pilot cohort HF preserved/mildly reduced ejection fraction (HFpEF/HFmrEF) whether PVR PCWP...

Introduction: Electrocardiography (ECG) is a quick and easily accessible method for diagnosis screening of cardiovascular diseases including heart failure (HF). Artificial intelligence (AI) can be used semi-automated ECG analysis. The aim this evaluation was to provide an overview AI use in HF detection from signals perform meta-analysis available studies. Methods Results: An independent comprehensive search the PubMed Google Scholar database conducted articles dealing with ability predict...

Abstract Ischaemic heart disease is among the most frequent causes of death. Early detection myocardial pathologies can increase benefit therapy and reduce number lethal cases. Presence scar an indicator for developing ischaemic be detected with high diagnostic precision by magnetic resonance imaging. However, imaging scanners are expensive limited availability. It known that presence has impact on well-established, reasonably low cost, almost ubiquitously available electrocardiogram. this...

Publications are only as strong the people who make them work. As part of this new chapter in IEEE Technology and Society Magazine (TSM), is first a series pieces to introduce associate editors represent powerhouse knowledge on social implications technology leaders from across many varied disciplines that for Social Implications (IEEE SSIT) encompasses. We hope answers below highlight ways which both scholars engaged citizens whose work aims positive change it addresses (or transforms)...

Recent activity in the field of artificial intelligence (AI) has given rise to large language models (LLMs) such as GPT-4 and Bard. These are undoubtedly impressive achievements, but they raise serious questions about appropriation, accuracy, explainability, accessibility, responsibility, more. There have been pusillanimous self-exculpating calls for a halt development by senior researchers largely self-serving comments industry leaders around potential AI systems, good or bad. Many these...

The specification and application of policies guidelines for public health, medical education training, screening programmes preventative medicine are all predicated on trust relationships between authorities, health practitioners patients. These in turn a verbal contract that is over two thousand years old. impact information communication technology (ICT), underpinning Health 4.0, has the potential to disrupt this analog relationship several dimensions; but it also presents an opportunity...

Intelligent AI systems using approaches containing emergent elements often encounter acceptance problems. Results do not get sufficiently explained and the procedure itself can be fully retraced because flow of control is dependent on stochastic elements. Trust in such algorithms must established so that users will accept results, without questioning whether algorithm sound. In this position paper we present an approach which user gets involved optimization by letting them chose alternative...

Domain-specific languages (DSLs) are a popular approach among software engineers who demand for tailored development interface. A DSL-based allows to encapsulate the intricacies of target platform in transformations that turn DSL models into executable code. Often, DSLs even claimed reduce complexity level them be successfully applied by domain-experts with limited programming knowledge. Recent research has produced some scientifically backed insights on benefits and limitations DSLs....

In this paper we present a new method for the extraction of discipline-specific terms from medical documents. Due to small text corpora and specific nature documents, there are limitations approaches that solely based on term frequencies. A combination such methods with procedures sensitive semantic aspects is therefore promising. We use word embeddings in neighborhood context which call Snowball because its layerwise way working. integrated together established into an end pipeline can...

In state of the art research a growing interest in application agent models for simulation road traffic can be observed. Software agents are particularly suitable representation travellers and their goal-oriented behaviour. Although numerous applications based on these types already available, options modelling calibration as individuals either simplified to aggregated parameters or associated with overly complex opaque implementation details. This makes it difficult reuse available models....

Abstract Location of acoustic emission (AE) events is one the main evaluation tools in AE analysis. Reliable location sources enables accurate investigation mechanisms that led to a crack material. It known errors are influenced by several factors, including accuracy elastic wave arrival time reading, geometric distribution sensors, and most importantly, physical properties propagation medium. The aim this study application neural network classify clustered events, which were detected during...

Intelligent information systems that contain emergent elements often encounter trust problems because results do not get sufficiently explained and the procedure itself can be fully retraced. This is caused by a control flow depending either on stochastic or structure relevance of input data. Trust in such algorithms established letting users interact with system so they explore find patterns compared their expected solution. Reflecting features human understanding domain against algorithmic...

Abstract Urban traffic is a system always prone to overload, often approaching breakdown during rush hour times. Well-adjusted modifications of policies, with appropriate interventions, promise potential improvements by inducing change in both individual as well global behaviour. However, truly effective measures are hard identify, and testing vivo at least expensive hardly feasible. Computer-based simulations have successfully been applied for studying effects multi-agent systems accepted...

Within business games there is a need to provide realistic feedback for decisions made, if such are continue remain relevant in increasingly complex environments.We address this problem by using so ware agents simulate individuals and model their actions response decisions.In our initial studies we have used consumers who make buying based on private preferences those prevalent within social network.This approach can be applied search behavioural patterns structures verify predicted values...

Automatic classification of documents is a well known problem and can be solved with Machine Learning methods. However, such approaches require large sets training data which are not always available. Moreover, in protection sensitive domains, e.g. electronic health records, models often cannot directly transferred to other environments. We present transfer learning method uses ontologies normalise the feature space text classifiers. With this we guarantee that trained do contain any person...