1,075 research outputs found

    Risk Prediction and Outcome Analysis

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    An evaluation of the development and implementation of a clinical guideline for nurse led extubation of adult coronary artery bypass graft patients

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    Research Question Does standardising nursing practice through the implementation of a clinical guideline for extubating adult cardiac surgical patients early improve patient care? Aims Evaluate the development and implementation of a clinical guideline for nurse-led extubation of adult cardiac surgical patients at one centre in the United Kingdom. Objectives Methods 1. Provide a systematic overview of the evidence base for early extubation (Hawkes et al., 2003). 2. Quantify the impact on professional practice of standardising care through the use of the guideline (interrupted time series (ITS». 3. Explore the results of the ITS and identify important factors for the successful implementation of the guideline (qualitative study). A mixed methods approach in a single case study was used. New evidence in the form of a systematic review, including a meta-analysis, of existing evidence for early extubation was used to meet Objective One. An ITS study was used to quantify the impact of implementing the guideline. The third objective was met through a qualitative study drawing on applied practitioner ethnography. The last two parts contribute unique evidence because there was no such existing evaluation of a nursing guideline for extubating cardiac surgical patients. Analysis The systematic review's meta-analysis used relative risk and weighted mean differences. The ITS analysis used exponential models to compare predicted values with actual values to assess the impact of the guideline. Qualitative data were analysed to identify themes, using the framework approach (Ritchie and Spencer, 1994). Results Early extubation reduces intensive care unit and hospital length of stay; the evidence for its impact on mortality and morbidity is weak. Evidence to support various decision making processes for early extubation is also lacking. The ITS demonstrated no changes in the outcomes studied. The guideline developed was a consensus of existing practice. However, while it did not change patient care, it maintained standards in a changing environment

    Artificial intelligence versus human intelligence in anaesthesia: who is winning?

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    Artificial intelligence (AI) plays a significant role especially in the light of the COVID-19 pandemic. The position of anaesthesiologists and their role in providing anaesthetic services initially was dominant. The AI ability to overtake the human’s capability in providing an accurate medical treatment may threaten the role of a doctor. The integration of AI in anaesthesia has been tremendous. Challenges in using this technology in anaesthesia are to determine, design, test the practicality, maintain dynamicity and market the technology. In the future, we hope AI may become the strongest weapon for anaesthesiologists to deliver the best anaesthesia services to patients and not as an enem

    NES2017 Conference Proceedings : JOY AT WORK

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    Efficient Decision Support Systems

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    This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

    Technologies and Applications for Big Data Value

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    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
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