A systematic literature review of data science, data analytics and machine learning applied to healthcare engineering systems

The objective of this paper is to assess and synthesize the published literature related to the application of data analytics, big data, data mining, and machine learning to healthcare engineering systems. A systematic literature review (SLR) was conducted to obtain the most relevant papers related to the research study from three different platforms: EBSCOhost, ProQuest, and Scopus. The literature was assessed and synthesized, conducting analysis associated with the publications, authors, and content. From the SLR, 576 publications were identified and analyzed. The research area seems to show the characteristics of a growing field with new research areas evolving and applications being explored. In addition, the main authors and collaboration groups publishing in this research area were identified throughout a social network analysis. This could lead new and current authors to identify researchers with common interests on the field. The use of the SLR methodology does not guarantee that all relevant publications related to the research are covered and analyzed. However, the authors’ previous knowledge and the nature of the publications were used to select different platforms. To the best of the authors’ knowledge, this paper represents the most comprehensive literature-based study on the fields of data analytics, big data, data mining, and machine learning applied to healthcare engineering systems.N/

Designing Data Spaces

This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II “Data Space Technologies” subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various “Use Cases and Data Ecosystems” from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several “Solutions and Applications”, eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty

The Rising Costs of Hospital Pharmaceutical Shortages and the Impact on Patient Care: Exploring the Use of Predictive Analytics in New York Area Hospitals

This qualitative case study examined the rising cost of hospital pharmaceutical shortages and the impact on patient care. This study also explored the use of predictive analytics to reduce costs and improve patient care efficiency. Increased health-care spending is partially due to prescription medication prices. Management of hospital drug procurement affects patient health, quality care, and hospital budgets, while risk management needs to minimize possible medication shortages. For patients to get the drugs that they need, pharmacists need to have resources at their fingertips to obtain a deep insight into the knowledge of drugs through the supply chain. The research questions concentrated on the causes of rising costs, the role of supply and demand, and the possibility of predictive analytics as a tool for inefficiencies relating to rising costs of hospital pharmaceutical shortages. The unexpected factor in this study was the impact of the Coronavirus (COVID-19) pandemic. Not only did COVID-19 alter the data collection method, but the data itself. Hospital pharmaceuticals were and still are greatly affected by the pandemic. The findings from this study was applied to the professional practice of business. Additionally, the researcher discussed the implication of the biblical worldview and the implication of the strategic management field of study. The report finished with suggestions for practice, suggestions for further analysis, reflections, and conclusions. The researcher also recommended that the study be conducted again with a specific pharmaceutical shortage and no global pandemic

Social Knowledge Creation: Three Annotated Bibliographies

In 2012-2013 a team led by Ray Siemens at the Electronic Textual Cultures Lab (ETCL), University of Victoria, in collaboration with Implementing New Knowledge Environments (INKE), developed three annotated bibliographies under the rubric of social knowledge creation. The items for the bibliographies were gathered and annotated by members of the Electronic Textual Cultures Lab (ETCL) to form this tripartite document as a resource for students and researchers involved in the iNKE team and well beyond, iincluding at digital humanities seminars in Bern (June 2013) and Leipzig (July 2013)

Cultural Heritage Leading Urban Futures: Actions and Innovations from ROCK Project

The ROCK project sees historic city centres as laboratories to demonstrate how Cultural Heritage can be an engine of regeneration, sustainable development and economic growth. ROCK approach foresees the systemic and flexible application of a series of role-model practices in the testing sites of three Replicator cities, to turn historic city centres afflicted by physical decay, social conflicts and poor life quality into Creative and Sustainable Districts. This book provides an overview of the project, extracting themes, material and final remarks from the Open Knowledge Week “Cultural Heritage Leading Urban Futuresâ€, held on 27-30 October 2020. Over the past three years, ten ROCK cities – Athens, Bologna, Cluj-Napoca, Eindhoven, Lisbon, Liverpool, Lyon, Skopje, Turin, and Vilnius â€“ together with service providers and knowledge brokers have tested and advanced numerous soft and hard tools, collaborative approaches aimed at shaping sustainable, heritage-led urban futures. This book shows their shared results, best practices and lessons learnt from interdisciplinary research, innovative action, dissemination of knowledge and creation of new synergies at European level

User Requirements in Enterprise Resource Planning Systems Adoption: A Case of Botswana’s Higher Institutions

ERP systems are the largest software applications adopted by universities, along with quite significant investments in their implementation. However, unlike other applications, limited research has been conducted regarding the application of this system in higher education in Botswana. This study aims to identify user requirements in the adoption of enterprise resource planning (ERP) systems in Botswana’s higher education institutions. This study was conducted in three higher education institutions in Botswana. This study adopted the quantitative methodology of using surveys to understand ERP adoption in higher education and proposed a model that could be used to guide business information systems requirements to appropriate ERP systems in a higher educational environment. Based on the findings, the study proposed a conceptual model of ERP system adoption in higher education institutions using six success dimensions. The six success dimensions are user requirements, user satisfaction, information quality, service quality, institutional impact, system quality, and faculty/management impact. Only information quality was rejected from the model. The six success dimensions are the basis through which a higher education institution can understand user requirements in implementing an effective ERP

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems