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Artificial intelligence (AI) is coming into the field of nuclear medicine, and it is likely here to stay. As a society, EANM can and must play a central role in the use of AI in nuclear medicine. In this position paper, the EANM explains the preconditions for the implementation of AI in NM and takes position. [ABSTRACT FROM AUTHOR]

Chatbots have experienced significant growth over the past decade, with a proliferation of new applications across various domains. Previous studies also demonstrate the trend of new technologies, especially artificial intelligence, being adopted in libraries. The purpose of this study is to determine the current research priorities and findings in the field of chatbots in libraries. A systematic literature review was performed utilising the PRISMA checklist and the databases Scopus and Web of Science, identifying 5734 records. Upon conducting the first screening, abstract screening, full-text assessment, and quality assessments guided by the CASP appraisal checklist, 19 papers were deemed suitable for inclusion in the review. The results of the review indicate that the majority of the existing studies were empirical in nature (primarily adopting qualitative methods) and technology reviews with a focus on reviewing the implementation and maintenance, design, evaluation, characteristics, and application of chatbots. The chatbots of interest were mainly text-based and guided chatbots, with closed-source tools with access portals mostly built on library web pages or integrated with social software. The research findings primarily concerned the development models and necessary tools and technologies, the application of chatbots in libraries. Our systematic review also suggests that studies on chatbots in libraries are still in the early stages. [This paper was presented at the 2023 Libraries in the Digital Age (LIDA) International Conference (Osijek, Croatia, May 24-26, 2023).]

Emergence and development of the blockchain technology, which is able to transform into "a most powerful disruptive innovation", shall definitely concern universities. Moreover, nowadays the blockchain technology meets the challenges that both the system of higher education and the entire society are currently facing. Advantages of the blockchain technology are decentralized open data, absence of forgeries, safe storage of information, and reduction of transaction expenses related to data checkup, control, and verification. This paper provides a critical analysis of application of the blockchain technology considering with its applicability opportunities and restrictions in education; it also aims to identify the consequences of its influence upon the development of education. The article analyzes real cases when this technology was applied, with the Massachusetts Institute of Technology (MIT) as an example. The MIT applied it to protect and validate the certificates that it issued. Another example is the Sony Global Education that forms individual data on its trainees' competencies and productivity; a third one relates to the University of Nicosia, which was the first to use smart contracts and accept cryptocurrency as a form of payment. The paper also considers the elements of the blockchain technology at universities (both in Russia and outside it), which participate in massive open online courses. It determines the scope of application of this technology in the Russian educational system. In addition, this article provides a literature review related to application of the blockchain technology; the review includes works by such renowned researchers as D. Tapscott, B. Bleir, A. Watters, A. Grech, A. Camilleri, M. Swan, A. Zaslavsky, etc. The paper analyzes the obtained findings of the survey that its authors have conducted among experts, professors, and specialists involved in accreditation. Thus, the paper provides an analysis of opportunities and restrictions related to application of the blockchain technology in higher education.

This paper presents a proposal of specific curriculum in Artificial Intelligence (AI) for high school students, which has been organized as a two-year subject. The curriculum was designed based on two premises. The first one is that, although the proposal is targeted to scientific programmes, the involved students and teachers do not have any previous knowledge about AI. Accordingly, the teaching units have been designed with the aim of supporting teachers in a new discipline for them and, in addition, providing an introductory level to students. The main didactical objective is to establish the fundamentals of AI from a practical perspective, learning technical concepts by using them to solve specific problems. The approach that has been followed in the teaching units is focused on developing embedded intelligence solutions, that is, programming real-world devices which interact with real environments. To this end, and to address a second fundamental premise of low investment capability at schools, it has been decided to use Smartphones as the central technological element to implement such embedded intelligence at classes. This curriculum has been developed within the Erasmus + project entitled "AI + : Developing an Artificial Intelligence Curriculum adapted to European High School". The project was carried out by a team of AI experts and high school teachers who created the teaching units, and a group of students that tested them for three years, providing feedback to make the curriculum feasible for its introduction in schools in the short-term. The main results obtained from its implementation within the project scope are presented and discussed here, with the aim of contributing to the AIEd community progress by means of a practical pilot experience. Although the curriculum has been designed and tested at European level, it has been created with a general perspective of AI education, so it can be applied worldwide.

Around a third of the total population of Europe suffers from mental disorders. The use of electroencephalography (EEG) together with Machine Learning (ML) algorithms to diagnose mental disorders has recently been shown to be a prominent research area, as exposed by several reviews focused on the field. Nevertheless, previous to the application of ML algorithms, EEG data should be correctly preprocessed and prepared via Feature Engineering (FE). In fact, the choice of FE techniques can make the difference between an unusable ML model and a simple, effective model. In other words, it can be said that FE is crucial, especially when using complex, non-stationary data such as EEG. To this aim, in this paper we present a Systematic Mapping Study (SMS) focused on FE from EEG data used to identify mental disorders. Our SMS covers more than 900 papers, making it one of the most comprehensive to date, to the best of our knowledge. We gathered the mental disorder addressed, all the FE techniques used, and the Artificial Intelligence (AI) algorithm applied for classification from each paper. Our main contributions are: (i) we offer a starting point for new researchers on these topics, (ii) we extract the most used FE techniques to classify mental disorders, (iii) we show several graphical distributions of all used techniques, and (iv) we provide critical conclusions for detecting mental disorders. To provide a better overview of existing techniques, the FE process is divided into three parts: (i) signal transformation, (ii) feature extraction, and (iii) feature selection. Moreover, we classify and analyze the distribution of existing papers according to the mental disorder they treat, the FE processes used, and the ML techniques applied. As a result, we provide a valuable reference for the scientific community to identify which techniques have been proven and tested and where the gaps are located in the current state of the art. [ABSTRACT FROM AUTHOR]

Small and medium-sized enterprises (SMEs) in Europe risk their competitiveness if they fail to embrace digitalization. Indeed, SMEs are aware of the need to digitalize--more than one in two SMEs are concerned that they may lose competitiveness if they do not adopt new digital technologies. However, a key obstacle is related with decision-makers' lack of awareness concerning digital technologies potential and implications. Some decision-makers renounce digital transition simply because they do not understand how it can be incorporated into the business. Take into account this common reality, especially among SMEs, this research project intends to identify the skills and subjects that need to be addressed and suggests the educational methodology and implementation strategy capable of maximizing its success. Therefore, and supported by a focused group research methodology, an innovative training program, oriented to decision-makers, was designed and implemented. The program was conceived based on a self-directed learning methodology, combining both asynchronous lecture/expositive and active training methodologies, strongly based on state-of-the-art knowledge and supported by reference cases and real applications. It is intended that the trainees/participants become familiar with a comprehensive set of concepts, principles, methodologies, and tools, capable of significantly enhancing decision-making capability at both strategic and tactical level. The proposed programme with a multidisciplinary scope explores different thematic chapters (self-contained) as well as cross-cutting thematic disciplines, oriented to the Industry 4.0 and digital transformation paradigm. Topics related with Digital Maturity Assessment, Smart Factories and Flexible Production Systems, Big Data, and Artificial Intelligence for Smarter Decision-Making in Industry and Smart Materials and Products, as well as new production processes for new business models. Each thematic chapter in turn is structured around a variable set of elementary modules and includes examples and case studies to illustrate the selected topics. A teaching-learning methodology centered on an online platform is proposed, having as a central element, a collection of videos complemented by a set of handouts that organize the set of key messages and take-ways associated with each module. In this paper, we present the design and practice of this training course specifically oriented to decision-makers in SME.

Research on Artificial Intelligence, especially in the field of machine learning, has exploded in the twenty-first century. AI research in universities has long been funded by a combination of government and corporate sources. The funding of AI research in the contemporary university includes technology companies as both funders and generators of research areas. This paper looks at the links between technology companies and AI research in three areas: first, the ways in which technology companies influence both the content and practices of AI research in universities; second, how university research policies enable conditions that blur traditional boundaries between corporate and academic AI research; and third, how an ethos of 'open science', that is increasingly corporatised, moves ideas about AI from universities to companies. We conclude that technology companies influence AI research within established feedback loops in the transformed relationships between economy, society, research, and the contemporary university.

Cardiac computed tomography (CT) was initially developed as a non-invasive diagnostic tool to detect and quantify coronary stenosis. Thanks to the rapid technological development, cardiac CT has become a comprehensive imaging modality which offers anatomical and functional information to guide patient management. This is the second of two complementary documents endorsed by the European Association of Cardiovascular Imaging aiming to give updated indications on the appropriate use of cardiac CT in different clinical scenarios. In this article, emerging CT technologies and biomarkers, such as CT-derived fractional flow reserve, perfusion imaging, and pericoronary adipose tissue attenuation, are described. In addition, the role of cardiac CT in the evaluation of atherosclerotic plaque, cardiomyopathies, structural heart disease, and congenital heart disease is revised. [ABSTRACT FROM AUTHOR]

Purpose: Major trauma remains a significant cause of morbidity and mortality in the developed and developing world. In 2013, nearly 5 million people worldwide died from their injuries, and almost 1 billion individuals sustained injuries that warranted some type of healthcare, accounting for around 10% of the global burden of disease in general. Behind the statistics, severe trauma takes a major toll on individuals, their families and healthcare systems. Management of the patient with severe trauma requires multiple interventions in a highly time-sensitive context and fragmentation of care, characterised by loss of information and time among disciplines, departments and individuals, both outside the hospital and within it, is frequent. Outcomes may be improved by better streamlining of pre- and intra-hospital care.Methods: We describe the basis for development of a multi-stakeholder consortium by the European Critical Care Foundation working closely with a number of European Scientific Societies to address and overcome problems of fragmentation in the care of patients with severe trauma.Result: The consortium will develop and introduce an information management system adapted to severe trauma, which will integrate continuous monitoring of vital parameters and point-of-care diagnostics. The key innovation of the project is to harness the power of information technologies and artificial intelligence to provide computer-enhanced clinical evaluation and decision-support to streamline the multiple points at which information and time are potentially lost.Conclusions: The severe trauma management platform thus created could have multiple benefits beyond its immediate use in managing the care of injured patients. [ABSTRACT FROM AUTHOR]

This paper examines the impact of Artificial Intelligence (AI) on early retirement (ER) decisions in Europe. For the analysis, we utilize microdata from the Survey of Health, Ageing and Retirement in Europe, along with occupation-level data on AI advances and AI exposure. Initially, we investigate the influence of AI advances and AI exposure separately, finding in both instances a significant reduction in ER likelihood, though this only applies to workers with higher education. Subsequently, we explore the interaction between AI advances and AI exposure concerning ER probability. This interaction proves critical in determining AI's impact on ER transitions. Specifically, we observe a significant reduction in ER probabilities for workers whose occupations exhibit high levels of AI advances and high expectations for further implementation of this technology in the future. Finally, we jointly analyse the interaction between AI advances, AI exposure, and education level. This analysis highlights that workers' ER probabilities may either increase or decrease in response to the AI revolution, depending on their education level and the characteristics of their occupations in terms of AI advances and AI exposure. [ABSTRACT FROM AUTHOR]

The European legal framework is not devoid of norms that are directly or indirectly applicable to facial recognition technology for identification purposes within law enforcement. However, these various norms, which have different targets and are from multiple sources, create a kind of legal patchwork that could undermine the lawful use of this technology in criminal investigations. This paper advocates the creation of a specific law on the use of facial recognition technology for identification in law enforcement, based on existing regulations, to specifically address the pressing issues arising in this domain. The ultimate aim is to allow its use under certain conditions and to protect the rights of the people involved, but also to provide law enforcement authorities with the necessary tools to combat serious crimes. [ABSTRACT FROM AUTHOR]

The application of artificial intelligence (AI) systems is emerging in many fields in recent years, due to the increased computing power available at lower cost. Although its applications in various branches of medicine, such as pediatric oncology, are many and promising, its use is still in an embryonic stage. The aim of this paper is to provide an overview of the state of the art regarding the AI application in pediatric oncology, through a systematic review of systematic reviews, and to analyze current trends in Europe, through a bibliometric analysis of publications written by European authors. Among 330 records found, 25 were included in the systematic review. All papers have been published since 2017, demonstrating only recent attention to this field. The total number of studies included in the selected reviews was 674, with a third including an author with a European affiliation. In bibliometric analysis, 304 out of the 978 records found were included. Similarly, the number of publications began to dramatically increase from 2017. Most explored AI applications regard the use of diagnostic images, particularly radiomics, as well as the group of neoplasms most involved are the central nervous system tumors. No evidence was found regarding the use of AI for process mining, clinical pathway modeling, or computer interpreted guidelines to improve the healthcare process. No robust evidence is yet available in any of the domains investigated by systematic reviews. However, the scientific production in Europe is significant and consistent with the topics covered in systematic reviews at the global level. The use of AI in pediatric oncology is developing rapidly with promising results, but numerous gaps and challenges persist to validate its utilization in clinical practice. An important limitation is the need for large datasets for training algorithms, calling for international collaborative studies. [ABSTRACT FROM AUTHOR]

This paper identifies and classifies the essential constraints that must be addressed to allow U-space traffic autonomous guidance. Based on an extensive analysis of the state of the art in robotic guidance, physics of flight, flight safety, communication and navigation, uncrewed aircraft missions, artificial intelligence (AI), social expectations in Europe on drones, etc., we analyzed the existing constraints and the information needs that are of essential importance to address the identified constraints. We compared the identified information needs with the last edition of the U-space Concept of Operations and identified critical gaps between the needs and proposed services. A high-level methodology to identify, measure, and close the gaps is proposed. [ABSTRACT FROM AUTHOR]

It is widely known that artificial intelligence is part of our lives. It is also generally feared that artificial intelligence has a potential to endanger human rights in this digital age. The paper intends to examine whether the European Court of Human Rights, dedicated to protecting human rights in Europe, has been forced to deal with artificial intelligence. The main focus of the analysis is the case law of the Court: after the identification of the human rights potentially in danger, the database of the Court's case law, HUDOC, has been screened by keyword search. Based on the examination of the jurisprudence, the paper will disclose if the Court has artificial intelligencerelated cases and attempts to predict whether it ever will. [ABSTRACT FROM AUTHOR]

This paper examines the ethical and legal challenges encountered during the GATEKEEPER Project and how these challenges informed the development of a comprehensive framework for future Large-Scale Pilot (LSP) projects. GATEKEEPER is a LSP Project with 48 partners conducting 30 implementation studies across Europe with 50,000 target participants grouped into 9 Reference Use Cases. The project underscored the complexity of obtaining ethical approval across various jurisdictions with divergent regulations and procedures. Through a detailed analysis of the issues faced and the strategies employed to navigate these challenges, this study proposes an ethical and legal framework. This framework, derived from a comparative analysis of ethical application forms and regulations, aims to streamline the ethical approval process for future LSP research projects. By addressing the hurdles encountered in GATEKEEPER, the proposed framework offers a roadmap for more efficient and effective project management, ensuring smoother implementation of similar projects in the future. [ABSTRACT FROM AUTHOR]

The intended automation in the financial industry creates a proper area for artificial intelligence usage. However, complex and high regulatory standards and rapid technological developments pose significant challenges in developing and deploying AI-based services in the finance industry. The regulatory principles defined by financial authorities in Europe need to be structured in a fine-granular way to promote understanding and ensure customer safety and the quality of AI-based services in the financial industry. This will lead to a better understanding of regulators' priorities and guide how AI-based services are built. This paper provides a classification pattern with a taxonomy that clarifies the existing European regulatory principles for researchers, regulatory authorities, and financial services companies. Our study can pave the way for developing compliant AI-based services by bringing out the thematic focus of regulatory principles. [ABSTRACT FROM AUTHOR]

Amid energy concerns due to the war in Europe and the reduction of energy reserves, how much are internet users and consumers positively influenced by a site with characteristics that indicate an environmentally friendly brand name? This paper presents strategies for creating an online eco-friendly brand name. In addition, with the help of an online artificial intelligence application, it examines traffic and other characteristics on business sites that adhere to some specific criteria such as eco-friendly logos, content, products and site design. [ABSTRACT FROM AUTHOR]

This paper considers recent experiments in art and artificial intelligence that crystallize around training algorithms to generate artworks based on datasets derived from the Western art historical canon. Over the last decade, a shift towards the rejection of canonicity has begun to take shape in art historical discourse. At the same time, algorithmically enabled practices in the US and Europe have emerged that entrench the Western canon as a locus and guarantor of aesthetic value. Operating within the epistemic framework of a "view from nowhere," this tendency in generative art inherits the coloniality of both art history and artificial intelligence. Producing "art histories from nowhere," this tendency conflates the conceptual category of visual art with the histories of Western cultural production. It reproduces a set of aesthetic values that entrench the mythology of the artist-genius and his imputed whiteness and masculinity; the extolment of innovation and novelty as self-evident virtues; disembodied Cartesian models of knowing and sensing; and the erasure of contributions that have been occluded from canonical visibility. As we encounter systems trained on particular visions of art history and of the artist, how might we remain attentive to the specific lens through which they are taught to see? This essay addresses that question by bringing the coloniality of recent experiments into view, bridging data feminisms and decolonial studies to formulate alternative visions of encounters between art and AI. [ABSTRACT FROM AUTHOR]

Virtual assistants (VAs) have gained widespread popularity across a wide range of applications, and the integration of Large Language Models (LLMs), such as ChatGPT, has opened up new possibilities for developing even more sophisticated VAs. However, this integration poses new ethical issues and challenges that must be carefully considered, particularly as these systems are increasingly used in public services: transfer of personal data, decision-making transparency, potential biases, and privacy risks. This paper, an extension of the work presented at IberSPEECH 2022, analyzes the current regulatory framework for AI-based VAs in Europe and delves into ethical issues in depth, examining potential benefits and drawbacks of integrating LLMs with VAs. Based on the analysis, this paper argues that the development and use of VAs powered by LLMs should be guided by a set of ethical principles that prioritize transparency, fairness, and harm prevention. The paper presents specific guidelines for the ethical use and development of this technology, including recommendations for data privacy, bias mitigation, and user control. By implementing these guidelines, the potential benefits of VAs powered by LLMs can be fully realized while minimizing the risks of harm and ensuring that ethical considerations are at the forefront of the development process. [ABSTRACT FROM AUTHOR]

Algorithmic decision-making and other types of artificial intelligence (AI) can be used to predict who will commit crime, who will be a good employee, who will default on a loan, etc. However, algorithmic decision-making can also threaten human rights, such as the right to non-discrimination. The paper evaluates current legal protection in Europe against discriminatory algorithmic decisions. The paper shows that non-discrimination law, in particular through the concept of indirect discrimination, prohibits many types of algorithmic discrimination. Data protection law could also help to defend people against discrimination. Proper enforcement of non-discrimination law and data protection law could help to protect people. However, the paper shows that both legal instruments have severe weaknesses when applied to artificial intelligence. The paper suggests how enforcement of current rules can be improved. The paper also explores whether additional rules are needed. The paper argues for sector-specific – rather than general – rules, and outlines an approach to regulate algorithmic decision-making. [ABSTRACT FROM AUTHOR]

Copyright of European Review of Public Law is the property of European Public Law Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Of all emerging technologies, Artificial Intelligence (AI) is perhaps the most debated topic in contemporary society because it promises to redefine and disrupt several sectors. At the same time, AI poses challenges for policymakers and decision-makers, particularly regarding formulating strategies and regulations to address their stakeholders' needs and perceptions. This paper explores stakeholder perceptions as expressed through their participation in the formulation of Europe's AI strategy and sheds light on the challenges of AI in Europe and the expectations for the future. Our analysis reveals six dimensions towards an AI strategy; ecosystems, education, liability, data availability sufficiency & protection, governance and autonomy. It draws on these dimensions to construct a desires-realities framework for AI strategy in Europe and provide a research agenda for addressing existing realities. Our findings contribute to understanding stakeholder desires on AI and hold important implications for research, practice and policymaking. [ABSTRACT FROM AUTHOR]

Background: Sustainable energy transition of a country is complex and long-term process, which requires decision-making in all stages and at all levels, including a large number of different factors, with different causality. The main objective of this paper is the development of a probabilistic model for decision-making in sustainable energy transition in developing countries of SE Europe. The model will be developed according to the specificities of the countries for which it is intended—SE Europe. These are countries where energy transition is slower and more difficult due to many factors: high degree of uncertainty, low transparency, corruption, investment problems, insufficiently reliable data, lower level of economic development, high level of corruption and untrained human resources. All these factors are making decision-making more challenging and demanding. Methods: Research was done by using content analysis, artificial intelligence methods, software development method and testing. The model was developed by using MSBNx—Microsoft Research's Bayesian Network Authoring and Evaluation Tool. Results: Due to the large number of insufficiently clear, but interdependent factors, the model is developed on the principle of probabilistic (Bayesian) networks of factors of interest. The paper presents the first model for supporting decision-making in the field of energy sustainability for the region of Southeastern Europe, which is based on the application of Bayesian Networks. Conclusion: Testing of the developed model showed certain characteristics, discussed in paper. The application of developed model will make it possible to predict the short-term and long-term consequences that may occur during energy transition by varying these factors. Recommendations are given for further development of the model, based on Bayesian networks. [ABSTRACT FROM AUTHOR]

The aim of this paper is to contribute technical arguments to the debate about the importance of health examination surveys and their continued use during the post-pandemic health financing crisis, and in the context of a technological innovation boom that offers new ways of collecting and analysing individual health data (e.g. artificial intelligence). Technical considerations demonstrate that health examination surveys make an irreplaceable contribution to the local availability of primary health data that can be used in a range of further studies (e.g. normative, burden-of-disease, care cascade, cost and policy impact studies) essential for informing several phases of the health planning cycle (e.g. surveillance, prioritization, resource mobilization and policy development). Examples of the use of health examination survey data in the World Health Organization (WHO) European Region (i.e. Finland, Italy, Malta and the United Kingdom of Great Britain and Northern Ireland) and the WHO Region of the Americas (i.e. Chile, Mexico, Peru and the United States of America) are presented, and reasons why health provider-led data cannot replace health examination survey data are discussed (e.g. underestimation of morbidity and susceptibility to bias). In addition, the importance of having nationally representative random samples of the general population is highlighted and we argue that health examination surveys make a critical contribution to external quality control for a country's health system by increasing the transparency and accountability of health spending. Finally, we consider future technological advances that can improve survey fieldwork and suggest ways of ensuring health examination surveys are sustainable in low-resource settings. [ABSTRACT FROM AUTHOR]

Digitalization is continuing facilitating our daily lives. The world is interconnected as never before, bringing close people, businesses, or other organizations. However, hackers are also coming close. New business and operational models require the collection and processing of massive amounts of data in real-time, involving utilization of complex information systems, large supply-chains, personal devices, etc. These impose several advantages for adversaries on the one hand (e.g., poorly protected or monitored elements, slow fashion of security updates/upgrades in components that gain little attention, etc.), and many difficulties for defenders on the other hand (e.g., administrate large and complex systems with high dynamicity) in this cyber-security interplay. Impactful attacks on ICT systems, critical infrastructures, and supply networks, as well as cyber-warfare are deriving the necessity for more effective defensives. This paper presents a swarm-intelligence solution for incident handling and response. Cyber Threat Intelligence (CTI) is continuously integrated in the system (i.e., MISP, CVEs, STIX, etc.), and Artificial Intelligence (AI)/Machine Learning (ML) are incorporated in the risk assessment and event evaluation processes. Several incident handling and response sub-procedures are automated, improving effectiveness and decreasing response time. Information concerning identified malicious activity is circulated back to the community (i.e., via the MISP information sharing platform) in an open loop. The proposal is applied in the supply-chain of healthcare organizations in Europe (considering also EU data protection regulations). Nevertheless, it is a generic solution that can be applied in any domain. [ABSTRACT FROM AUTHOR]

Artificial intelligence and machine learning are revolutionising fields of science and engineering. In recent years, process engineering has widely benefited from this novel modelling and optimisation approach. The open literature can offer several examples of their applications to chemical engineering problems. Increasing investments are devoted to these techniques from different industrial areas, but insufficient information on a structured course covering these topics in a chemical engineering curriculum could be found. The course in this paper intends to reduce this gap. We introduce one of the first courses on artificial intelligence applications in a chemical engineering curriculum. The course targets Master's students with a chemical engineering background and insufficient knowledge of statistical approaches. It covers the main aspects by utilising frontal lectures and hands-on exercises with active learning methods. This paper shows the methodology we adapted to introduce students to machine learning techniques and how they responded to each class. The student performances for each test are shown, as well as the survey results based on student feedback and suggestions. This work contains essential guidelines for educators who will provide an artificial intelligence course in a chemical engineering curriculum. • An AI course for chemical engineers is given as one of the first attempts in Europe. • The course is structured into frontal and hands-on lessons. • Modelling and optimisation techniques via AI were shown to the students. • Applications of developed models were explained to the students. • Students can apply basic AI in chemical engineering tasks after this course. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has started to impact many facets of the economy and people's routine activities. This article contributes to our understanding of how the legal system is reacting to the ongoing uptake of AI and the disputes or right infringements this uptake creates. Select legal cases regarding the use of AI technology for automated decisions are reviewed, with a focus on filings in Europe and the USA. This exercise reveals which type of legal challenges can be expected when it comes to deploying automated systems in these jurisdictions. Additionally, incipient regulatory efforts targeting AI on both sides of the North Atlantic are introduced and briefly discussed. The paper sheds light on how different legal systems accommodate an emerging technology with disruptive potential and offers a mapping of exemplary legal risks for prospective actors or organisations seeking to develop and deploy AI. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) carries the potential for unprecedented disruption in radiology, with possible positive and negative consequences. The integration of AI in radiology holds the potential to revolutionize healthcare practices by advancing diagnosis, quantification, and management of multiple medical conditions. Nevertheless, the ever‑growing availability of AI tools in radiology highlights an increasing need to critically evaluate claims for its utility and to differentiate safe product offerings from potentially harmful, or fundamentally unhelpful ones. This multi‑society paper, presenting the views of Radiology Societies in the USA, Canada, Europe, Australia, and New Zealand, defines the potential practical problems and ethical issues surrounding the incorporation of AI into radiological practice. In addition to delineating the main points of concern that developers, regulators, and purchasers of AI tools should consider prior to their introduction into clinical practice, this statement also suggests methods to monitor their stability and safety in clinical use, and their suitability for possible autonomous function. This statement is intended to serve as a useful summary of the practical issues which should be considered by all parties involved in the development of radiology AI resources, and their implementation as clinical tools. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is set to redefine how farming occurs. Throughout history examples of technological advances have shown that less labour has been required on a farm while at the same time increasing the output of food production. However, an interesting observation is that as technology has improved the farming process and replaced workers, it has opened a new avenue known as diversification. This paper focuses specifically on the impact that AI will have on the future of farming in the European sector. The literature brings to light common trends that technological innovations have always decreased the number of workers required in the farming process while at the same time maximising efficiency. AI will also follow the same trend, however, instead of eliminating workers in the farming process soon, the present observations show that farmers will still require workers to work alongside AI. The reason for increased investments in AI is due to research data showing a decline in population growth in Europe and the struggling profitability of farmers. Thereby analysts believe that a labour shortage will occur, and industries will struggle to fill those skills requirements. A qualitative summary was done on artificial intelligence technologies' development impact on the labour of the agricultural sector of Europe. [ABSTRACT FROM AUTHOR]

Research performed in Europe has driven cardiovascular device innovation. This includes, but is not limited to, percutaneous coronary intervention, cardiac imaging, transcatheter heart valve implantation, and device therapy of cardiac arrhythmias and heart failure. An important part of future medical progress involves the evolution of medical technology and the ongoing development of artificial intelligence and machine learning. There is a need to foster an environment conducive to medical technology development and validation so that Europe can continue to play a major role in device innovation while providing high standards of safety. This paper summarizes viewpoints on the topic of device innovation in cardiovascular medicine at the European Society of Cardiology Cardiovascular Round Table, a strategic forum for high-level dialogue to discuss issues related to the future of cardiovascular health in Europe. Devices are developed and improved through an iterative process throughout their lifecycle. Early feasibility studies demonstrate proof of concept and help to optimize the design of a device. If successful, this should ideally be followed by randomized clinical trials comparing novel devices vs. accepted standards of care when available and the collection of post-market real-world evidence through registries. Unfortunately, standardized procedures for feasibility studies across various device categories have not yet been implemented in Europe. Cardiovascular imaging can be used to diagnose and characterize patients for interventions to improve procedural results and to monitor devices long term after implantation. Randomized clinical trials often use cardiac imaging-based inclusion criteria, while less frequently trials randomize patients to compare the diagnostic or prognostic value of different modalities. Applications using machine learning are increasingly important, but specific regulatory standards and pathways remain in development in both Europe and the USA. Standards are also needed for smart devices and digital technologies that support device-driven biomonitoring. Changes in device regulation introduced by the European Union aim to improve clinical evidence, transparency, and safety, but they may impact the speed of innovation, access, and availability. Device development programmes including dialogue on unmet needs and advice on study designs must be driven by a community of physicians, trialists, patients, regulators, payers, and industry to ensure that patients have access to innovative care. [ABSTRACT FROM AUTHOR]

Copyright of Archaeology & Science / Arheologija i Prirodne Nauke is the property of Institute of Archaeology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The European patent system was designed around a paradigm of human inventorship. This paper will analyse in depth and from a de lege ferenda perspective the rather general arguments against and in favour of a possible designation of artificial intelligence (AI) systems as inventors. For the sake of a more concrete discussion, it will also outline a potential reform of the European patent system to implement AI inventorship and allocate the right to the European patent for such inventions by default to the machine's operator. In the process, it will highlight the major specific issues associated with a reform that acknowledges AI inventorship and touch upon possible alternative approaches to addressing the growing autonomy of machines within the R&D process. The study must not be understood as a call for a reform to recognise AI systems as inventors but rather as a manner of laying the foundations for a more concrete, critical and fruitful discussion on non-human inventorship and its alternatives. The analysis will show that the more general, highly conceptional reservations advanced in the current discussion against AI inventorship are somewhat unfounded, e.g. the alleged break with the functions of the current patent system or the alleged need to endow AI with legal personality. More convincing arguments against a reform that allows for the designation of AI systems as inventor might instead relate to the specific difficulties associated with such reform. [ABSTRACT FROM AUTHOR]

Concrete is a mass commodity with more than approx. 250 Mio. batches of concrete being produced every year in Europe alone. Despite this enormous repetition rate, both the quality inspection of the concrete raw materials as well as of the mixed concrete are still primarily batch‐based, relying on manual processes, thus hindering the application of modern process control schemes. The reasons for this lack are on the one hand to be seen in the lack of suitable sensor technologies and on the other hand in missing control algorithms. The paper at hand gives an overview on the current state of the art sensor technologies for both raw material as well as concrete properties measurement. Further, it outlines a pathway towards an online concrete process control. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to examine the key intellectual and influential aspects of financial technology literature? and to evaluate the future research direction of financial technology literature? Design/methodology/approach: This paper adopts multiple software packages were employed, including Excel, VOSviewer and RStudio. VOSviewer is used to build networks of scientific articles, journals, researchers, organizations, countries, and terms. Findings: the analysis of the Bibliographical focusing on sources, depends on five clusters, the Sustainability (Switzerland), Financial Innovations, Investment Management, Europe journal of finance and Electronic Commerce Research and Applications the lead journals in the clusters. Originality: This paper contributes to the literature based on 4 classes of research streams in Fintech namely Fintech, blockchain, Artificial intelligence and Innovation which are represent the most future upcoming trends [ABSTRACT FROM AUTHOR]

Diabetic macular edema (DME) remains the major cause of preventable blindness in the working-age population in developed countries, and screening programs are extremely important in the management of this complication of diabetic retinopathy. The introduction of modern imaging modalities and technological advances have facilitated both the early detection and the follow-up of patients with DME, particularly optical coherence tomography angiography and artificial intelligence. Intravitreal therapy is the gold standard treatment for DME, but not all patients respond equally to this therapy, and sometimes it is not easy to apply treatment protocols correctly; for these reasons, clinical practice results may differ from those of clinical trials in terms of vision gain. One approach has been to implement new treatment regimens, such as treat and extend, and new molecules and therapeutic targets are constantly being developed. The main goal of this review paper is to describe the current treatment options and management strategies for DME in Europe and to provide a brief oversight of the novel therapeutic options on the horizon. [ABSTRACT FROM AUTHOR]

The Patient Advisory Group (PAG) of the European Society of Radiology aims to highlight, in this short paper, patients' expectations from the radiological community and support workers, throughout the patient's medical imaging journey for completion of diagnostic or interventional examinations. In order to maintain constant awareness of patients' expectations, key expectations have been summarised in an easy-to-remember mnemonic: PATIENTS CARERS AIMS. Due to disparate healthcare systems and medical imaging services in Europe, not all patient expectations can be systematically met, but healthcare providers should be mindful, when setting up new operational procedures, of the need to focus on patient-centred needs and care. At times when new or improved technology is being introduced, such as artificial intelligence applications, telemedicine, robotisation of interventional procedures and digitised records, the impact on radiologist–patient communication and interactions should be considered. [ABSTRACT FROM AUTHOR]

In papers using artificial intelligence (AI) techniques, little attention has been paid to the determinants of sovereign debt ratings. We propose a reduced set of variables regarding the economic performance of a country that are consistent with the idea of debt sustainability. The robustness of this set is supported by the results obtained with different well-known AI techniques using data from EU-15 countries during the 2002–2017 period as the experimental setting. The variables are publicly available, allowing a quick and reliable assessment of the creditworthiness of a sovereign and providing useful information for decision-makers and investors. [ABSTRACT FROM AUTHOR]

Advances in technology and science have led to the application of artificial intelligence in many different areas of life. In particular, they have led to the appearance of robots in the domestic sphere. One type of robot - namely, the social robot - has been endowed with a very human aesthetic and is designed to interact with humans, and it is increasingly being used to perform "human tasks". Social robots have also been introduced into the social services, providing companionship and assistive services for children, the infirm and the elderly. Such usage has rightly attracted the interest of the social sciences, fuelling the debate about the acceptance of social robots by their end-users. In this paper, regression analysis is applied to data from the Eurobarometer survey to investigate how socio-demographic features and self-confidence on technological development influence European citizens' attitudes towards robots in the social services. The results show that men, with a high level of education, living in a big city and with experience of robot use have more positive attitudes towards the concept of robots for assistive services. This study emphasizes the need to consider the relation between attitudes towards social robots and their use to avoid the generation of social inequalities. [ABSTRACT FROM AUTHOR]

Editor’s note: This article was written before the publication by the EU Commission of its proposal for an artificial intelligence (AI) regulation. In a first and provisional analysis of the proposed regulation, we observe that the proposed regulation incorporates some of the basic principles laid down in our article: it prioritizes fundamental rights and incorporates some human rights principles, such as accountability, and the inclusion of governance through supervisory authorities to implement and enforce the regulation. Nevertheless, we still feel that many of the suggestions present in our article, which would help to operationalize the regulation, are not addressed. One example is the reduced scope of the regulation to a list of “high risk applications,” leaving without a legal framework all other AI applications. We believe that the principles that inspire the regulation should also be applied in “lower risk applications.” Defining only the compliance process for AI developers, but leaving open the specific technical requirements that these high risk applications shall meet leaves untouched the existing gap between legal language and engineering practice. There are no described mechanisms by which all stakeholders (other than developers and implementers) can influence AI development, monitor their performance or claim redress if harmed. These shortcomings and other issues presented in our article leave the door open to loopholes that we hope the European Parliament can fix during the legislative process. [ABSTRACT FROM AUTHOR]

The starting point for this particular research is to uncover the relationship between the establishment of the regulatory framework, the implementation of various European digitisation development programmes and other types of enabling environment (financial instruments and programmes) with the demonstrated performance of business and science in the form of registered patents in the field of AI. The scope of the study is limited to the specific legal documents in the field of artificial intelligence, the financial mechanisms that Europe applies to stimulate research in this field, as well as to the applications filed and patents granted for technologies in the field of artificial intelligence, namely: machine understanding technologies. The study’s main results show that technology companies follow their own technology policies to meet market demands and trends, and support mechanisms (in the form of policies, programmes, and financial incentives) are more the result of technological developments than the other way around. [ABSTRACT FROM AUTHOR]

In a case study approach, the paper traces how technological expectations have been influential in the creation of European institutions, R&D programmes and regulatory instruments and how they have contributed to processes of European integration. The first case study shows how the promises of a coming 'Atomic Age' have been mobilized to support the foundation of the European Atomic Energy Community and, thus, contributed to European integration in the post-WW2 era. The second case study analyses how the security stream within the EU's framework programmes for R&D is shaped by the promise of 'technosecurity' and enacts the normative claim of the EU's security integration in the post-Cold War era. The third case study analyses how the EU's AI strategy and AI act articulate the vision of a 'human-centric AI' and how this vision is related to the EU's current attempt to restore citizens' trust in times of crisis. [ABSTRACT FROM AUTHOR]

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The European Union's recently adopted Artificial Intelligence (AI) Act is the first comprehensive legal framework specifically on AI. This is particularly important for the healthcare domain, as other existing harmonisation legislation, such as the Medical Device Regulation, do not explicitly cover medical AI applications. Given the far-reaching impact of this regulation on the medical AI sector, this commentary provides an overview of the key elements of the AI Act, with easy-to-follow references to the relevant chapters. [ABSTRACT FROM AUTHOR]

BACKGROUND: The assessment of bone age and skeletal maturity and its comparison to chronological age is an important task in the medical environment for the diagnosis of pediatric endocrinology, orthodontics and orthopedic disorders, and legal environment in what concerns if an individual is a minor or not when there is a lack of documents. Being a time-consuming activity that can be prone to inter- and intra-rater variability, the use of methods which can automate it, like Machine Learning techniques, is of value. OBJECTIVE: The goal of this paper is to present the state of the art evidence, trends and gaps in the research related to bone age assessment studies that make use of Machine Learning techniques. METHOD: A systematic literature review was carried out, starting with the writing of the protocol, followed by searches on three databases: Pubmed, Scopus and Web of Science to identify the relevant evidence related to bone age assessment using Machine Learning techniques. One round of backward snowballing was performed to find additional studies. A quality assessment was performed on the selected studies to check for bias and low quality studies, which were removed. Data was extracted from the included studies to build summary tables. Lastly, a meta-analysis was performed on the performances of the selected studies. RESULTS: 26 studies constituted the final set of included studies. Most of them proposed automatic systems for bone age assessment and investigated methods for bone age assessment based on hand and wrist radiographs. The samples used in the studies were mostly comprehensive or bordered the age of 18, and the data origin was in most of cases from United States and West Europe. Few studies explored ethnic differences. CONCLUSIONS: There is a clear focus of the research on bone age assessment methods based on radiographs whilst other types of medical imaging without radiation exposure (e.g. magnetic resonance imaging) are not much explored in the literature. Also, socioeconomic and other aspects that could influence in bone age were not addressed in the literature. Finally, studies that make use of more than one region of interest for bone age assessment are scarce. [ABSTRACT FROM AUTHOR]

Autonomous Vehicles (AV) technology is emerging. Field tests on public roads have been on going in several states in the US as well as in Europe and Asia. During the US public road tests, crashes with AV involved happened, which becomes a concern to the public. Most previous studies on AV safety relied heavily on assessing drivers’ performance and behaviors in a simulation environment and developing automated driving system performance in a closed field environment. However, contributing factors and the mechanism of AV-related crashes have not been comprehensively and quantitatively investigated due to the lack of field AV crash data. By harnessing California’s Report of Traffic Collision Involving an Autonomous Vehicle Database, which includes the AV crash data from 2014 to 2018, this paper investigates by far the most current and complete AV crash database in the US using statistical modeling approaches that involve both ordinal logistic regression and CART classification tree. The quantitative analysis based on ordinal logistic regression and CART models has successfully explored the mechanism of AV-related crash, via both perspectives of crash severity and collision types. Particularly, the CART model reveals and visualize the hierarchical structure of the AV crash mechanism with knowledge of how these traffic, roadway, and environmental contributing factors can lead to crashes of various serveries and collision types. Statistical analysis results indicate that crash severity significantly increases if the AV is responsible for the crash. The highway is identified as the location where severe injuries are likely to happen. AV collision types are affected by whether the vehicle is on automated driving mode, whether the crashes involve pedestrians/cyclists, as well as the roadway environment. The method used in this research provides a proven approach to statistically analyze and understand AV safety issues. And this benefit is potential be even enhanced with an increasing sample size of AV-related crashes records in the future. The comprehensive knowledge obtained ultimately facilitates assessing and improving safety performance of automated vehicles. [ABSTRACT FROM AUTHOR]