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| artificial intelligence in nursing education: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| artificial intelligence in nursing education: Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky Andrew M. Olney, |
| artificial intelligence in nursing education: New Developments in Nursing Education Research Tod S. Emerson, 2015 Caring is a highly complex and abstract concept, and nurturing a caring attribute among individuals for a nursing career is believed to be best introduced at the start of the student journey in preparatory courses specifically designed for nursing. However, because of the need to professionalize nursing, pre-enrolled nursing programs have been discontinued and replaced by generic healthcare programs in many parts of the world. This book provides a discussion on new developments in nursing education research. Topics include caring attributes and preparedness to care; behavior in interprofessional learning; undergraduate nursing curricula; the AARCA resolution model in addressing bullying of student nurses; and the establishment of a first year experience coordinator role for nursing students. |
| artificial intelligence in nursing education: Artificial Intelligence in Education Ning Wang, Genaro Rebolledo-Mendez, Noboru Matsuda, Olga C. Santos, Vania Dimitrova, 2023-06-25 This book constitutes the refereed proceedings of the 24th International Conference on Artificial Intelligence in Education, AIED 2023, held in Tokyo, Japan, during July 3-7, 2023. This event took place in hybrid mode. The 53 full papers and 26 short papers presented in this book were carefully reviewed and selected from 311 submissions. The papers present result in high-quality research on intelligent systems and the cognitive sciences for the improvement and advancement of education. The conference was hosted by the prestigious International Artificial Intelligence in Education Society, a global association of researchers and academics specializing in the many fields that comprise AIED, including, but not limited to, computer science, learning sciences, and education. |
| artificial intelligence in nursing education: Code of Ethics for Nurses with Interpretive Statements American Nurses Association, 2001 Pamphlet is a succinct statement of the ethical obligations and duties of individuals who enter the nursing profession, the profession's nonnegotiable ethical standard, and an expression of nursing's own understanding of its commitment to society. Provides a framework for nurses to use in ethical analysis and decision-making. |
| artificial intelligence in nursing education: Engineering Applications of Artificial Intelligence Aziza Chakir, |
| artificial intelligence in nursing education: Fundamentals of Canadian Nursing Barbara J. Kozier MN, RN, Glenora Erb BScN, RN, Audrey T. Berman, Shirlee Snyder, Madeleine Buck RN, BScN, MScN, Lucia Yiu RN, BSc, BA, MScN, Lynnette Leeseberg Stamler RN, PhD, 2013-03-05 Note: If you are purchasing an electronic version, MyNursingLab does not come automatically packaged with it. To purchase MyNursingLab, please visit www.mynursinglab.com or you can purchase a package of the physical text and MyNursingLab by searching for ISBN 10: 0133249786 / ISBN 13: 9780133249781. Helping undergraduate students evolve into nursing professionals prepared to meet the demands of their vocation, Fundamentals of Canadian Nursing equips students with a broad and solid foundation. The third Canadian edition addresses the key concepts that nurses must know to practice knowledgeably, accurately, legally, ethically, and with sensitivity and compassion in the dynamic Canadian health care system. Fundamentals of Canadian Nursing focuses on 3 important tenets: process, such as critical thinking, clinical reasoning, decision making; concepts like health promotion, disease prevention, and caring; and skills, such as health assessment, hygiene, and safety. Additionally, the textbook highlights basic nursing care across the lifespan in a variety of settings. Written in clear and accessible language, beginning nurses learn about best practices with real-world applications from the experts. Representing a pan-Canadian experience, the lead editors enlisted two authors, each from different provinces to reflect different geographical experiences, for many chapters. Special features facilitate learning and highlight the 5 major themes that form the framework for this edition–Primary Health Care, Critical Thinking, Clinical Reasoning, Nursing Process, and Lifespan Considerations. Important Notice: The digital edition of this book is missing some of the images found in the physical edition. |
| artificial intelligence in nursing education: Emerging Technologies for Nurses Whende M. Carroll, MSN, RN-BC, 2020-02-01 Learn and innovate with the latest technologies in nursing and healthcare! The first text of its kind in nursing, this book provides up-to-date information on innovative, smart technologies that nurses can use in clinical and nonclinical settings to keep up with the changing face of healthcare. This compelling guide will provide you with information about exciting areas of technology that have great potential to improve patient care. Subjects include big data, artificial intelligence, virtual and augmented realities, connected technologies, and precision health. There is also discusson of the shift of healthcare delivery into the community, with an outlook on improving outcomes and enhancing practice. Each chapter focuses on developing competency in current and future real-world applications of emerging technologies. Early chapters describe how to utilize new tools, processes, models, and products to serve the quadruple aim of better managing populations, decreasing costs, and enhancing both the patient’s and the clinician’s experience. The culture of innovation coincides with the ever-changing politics of healthcare in later chapters, which then evolves into the entrepreneurial opportunities for nurses. This text is an essential introduction for all practicing nurses, nurse leaders, and nurses teaching health information technology or informatics courses. Key Features: Written by nurses for nurses The latest information on emerging health information technology and associated nursing implications Compelling cases show the dramatic effect of innovations on value-based care Learn how applying novel technologies can improve patient care Qualified instructors have access to supplementary materials, including PowerPoint slides and an Instructor’s Manual |
| artificial intelligence in nursing education: Virtual and Augmented Reality in Education, Art, and Museums Guazzaroni, Giuliana, Pillai, Anitha S., 2019-11-22 Due to the growing prevalence of artificial intelligence technologies, schools, museums, and art galleries will need to change traditional ways of working and conventional thought processes to fully embrace their potential. Integrating virtual and augmented reality technologies and wearable devices into these fields can promote higher engagement in an increasingly digital world. Virtual and Augmented Reality in Education, Art, and Museums is an essential research book that explores the strategic role and use of virtual and augmented reality in shaping visitor experiences at art galleries and museums and their ability to enhance education. Highlighting a range of topics such as online learning, digital heritage, and gaming, this book is ideal for museum directors, tour developers, educational software designers, 3D artists, designers, curators, preservationists, conservationists, education coordinators, academicians, researchers, and students. |
| artificial intelligence in nursing education: Understanding Artificial Intelligence Ralf T. Kreutzer, Marie Sirrenberg, 2019-09-25 Artificial Intelligence (AI) will change the lives of people and businesses more fundamentally than many people can even imagine today. This book illustrates the importance of AI in an era of digitalization. It introduces the foundations of AI and explains its benefits and challenges for companies and entire industries. In this regard, AI is approached not just as yet another technology, but as a fundamental innovation, which will spread into all areas of the economy and life, and will disrupt business processes and business models in the years to come. In turn, the book assesses the potential that AI holds, and clarifies the framework that is necessary for pursuing a responsible approach to AI. In a series of best-practice cases, the book subsequently highlights a broad range of sectors and industries, from production to services; from customer service to marketing and sales; and in industries like retail, health care, energy, transportation and many more. In closing, a dedicated chapter outlines a roadmap for a specific corporate AI journey. No one can ignore intensive work with AI today - neither as a private person, let alone as a top performer in companies. This book offers a thorough, carefully crafted, and easy to understand entry into the field of AI. The central terms used in the AI context are given a very good explanation. In addition, a number of cases show what AI can do today and where the journey is heading. An important book that you should not miss! Professor Dr. Harley Krohmer University of Bern Inspiring, thought provoking and comprehensive, this book is wittingly designed to be a catalyst for your individual and corporate AI journey.” Avo Schönbohm, Professor at the Berlin School of Economics and Law, Enterprise Game Designer at LUDEO and Business Punk |
| artificial intelligence in nursing education: Nursing and Informatics for the 21st Century Charlotte Weaver, Connie Delaney, Patrick Weber, Robyn Carr, 2010-02-22 Nursing and Informatics for the 21st Century is the follow-up to the highly successful, award-winning first edition. Published in 2006, the first edition was a critical resource in chronicling the huge historical shift in nursing linked to the explosion of EHR national strategies and health policies around the globe. This updated edition, co-publis |
| artificial intelligence in nursing education: Compassion and Caring in Nursing Claire Chambers, Elaine Ryder, 2018-05-08 'Compassion, in its many manifestations, is the key to rediscovering what lies at the heart of nursing practice all over the world. It is absolutely essential that nurses start to revisit compassion as a central focus for nursing practice...' This user-friendly book adopts a patient-centred approach to care. The challenging theories are grounded in practical applications, encouraging readers to recognise opportunities for change in their daily practice. The book focuses on six key concepts central to compassionate care: A* |
| artificial intelligence in nursing education: Artificial Intelligence in Medicine David Riaño, Szymon Wilk, Annette ten Teije, 2019-06-19 This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning. |
| artificial intelligence in nursing education: Artificial Intelligence in Education Ben Du Boulay, R. Mizoguchi, 1997 The theme of this book is Knowledge and Media in Learning Systems, and papers that explore the emerging roles of intelligent multimedia and distributed technologies as well as computer supported collaboration within that theme are included. The spread of topics is very wide encompassing both well- established areas such as student modelling as well as more novel topics such as distributed intelligent tutoring on the World Wide Web. Far from undermining the need to understand how learning and teaching interact, the newer media continue to emphasise the interdependence of these two processes. Collaboration and tools for collaboration are the major topics of interest. Understanding how human learners collaborate, how peer tutoring works and how the computer can play a useful role as either a more able of even a less able learning partner are all explored here. |
| artificial intelligence in nursing education: Nursing Education Jennifer Boore, Patrick Deeny, 2012-09-18 Nursing Education provides a strategic guide and practical focus to curriculum planning and development. It will help all those involved in the provision of nursing education to understand the issues involved at the different stages of preparing a nursing curriculum which: - meets both professional and academic requirements; - integrates theory and practice; - enables students to achieve the skills and competencies they need for professional practice; - includes different methods of teaching and learning; - provides clear guidance for student selection and assessment. Balancing theoretical principles with practical application, and linked closely to the NMC′s 2010 standards for pre-registration nursing, Jennifer Boore and Pat Deeny illustrate clearly and accessibly how to develop tailored education programmes so that nurse educators and clinicians in practice can enable their students to provide up-to-date and appropriate patient care. |
| artificial intelligence in nursing education: Foundations of Artificial Intelligence in Healthcare and Bioscience Louis J. Catania, 2020-11-25 Foundational Handbook of Artificial Intelligence in Healthcare and Bioscience: A User Friendly Guide for IT Professionals, Healthcare Providers, Researchers, and Clinicians uses color-coded illustrations to explain AI from its basics to modern technologies. Other sections cover extensive, current literature research and citations regarding AI's role in the business and clinical aspects of health care. The book provides readers with a unique opportunity to appreciate AI technology in practical terms, understand its applications, and realize its profound influence on the clinical and business aspects of health care. Artificial Intelligence is a disruptive technology that is having a profound and growing influence on the business of health care as well as medical diagnosis, treatment, research and clinical delivery. The AI relationships in health care are complex, but understandable, especially when discussed and developed from their foundational elements through to their practical applications in health care. - Provides an illustrated, foundational guide and comprehensive descriptions of what Artificial Intelligence is and how it functions - Integrates a comprehensive discussion of AI applications in the business of health care - Presents in-depth clinical and AI-related discussions on diagnostic medicine, therapeutic medicine, and prevalent disease categories with an emphasis on immunology and genetics, the two categories most influenced by AI - Includes comprehensive coverage of a variety of AI treatment applications, including medical/pharmaceutical care, nursing care, stem cell therapies, robotics, and 10 common disease categories with AI applications |
| artificial intelligence in nursing education: Artificial Intelligence in Medicine Lei Xing, Maryellen L. Giger, James K. Min, 2020-09-03 Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. - Provides history and overview of artificial intelligence, as narrated by pioneers in the field - Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence - Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach |
| artificial intelligence in nursing education: Artificial Intelligence in Behavioral and Mental Health Care David D. Luxton, 2015-09-10 Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings |
| artificial intelligence in nursing education: The Future of Nursing 2020-2030 National Academies of Sciences Engineering and Medicine, Committee on the Future of Nursing 2020-2030, 2021-09-30 The decade ahead will test the nation's nearly 4 million nurses in new and complex ways. Nurses live and work at the intersection of health, education, and communities. Nurses work in a wide array of settings and practice at a range of professional levels. They are often the first and most frequent line of contact with people of all backgrounds and experiences seeking care and they represent the largest of the health care professions. A nation cannot fully thrive until everyone - no matter who they are, where they live, or how much money they make - can live their healthiest possible life, and helping people live their healthiest life is and has always been the essential role of nurses. Nurses have a critical role to play in achieving the goal of health equity, but they need robust education, supportive work environments, and autonomy. Accordingly, at the request of the Robert Wood Johnson Foundation, on behalf of the National Academy of Medicine, an ad hoc committee under the auspices of the National Academies of Sciences, Engineering, and Medicine conducted a study aimed at envisioning and charting a path forward for the nursing profession to help reduce inequities in people's ability to achieve their full health potential. The ultimate goal is the achievement of health equity in the United States built on strengthened nursing capacity and expertise. By leveraging these attributes, nursing will help to create and contribute comprehensively to equitable public health and health care systems that are designed to work for everyone. The Future of Nursing 2020-2030: Charting a Path to Achieve Health Equity explores how nurses can work to reduce health disparities and promote equity, while keeping costs at bay, utilizing technology, and maintaining patient and family-focused care into 2030. This work builds on the foundation set out by The Future of Nursing: Leading Change, Advancing Health (2011) report. |
| artificial intelligence in nursing education: Clinical Reasoning in the Health Professions Joy Higgs, Mark A Jones, Stephen Loftus, PhD, MSc, BDS, Nicole Christensen, 2008-02-14 Clinical reasoning is the foundation of professional clinical practice. Totally revised and updated, this book continues to provide the essential text on the theoretical basis of clinical reasoning in the health professions and examines strategies for assisting learners, scholars and clinicians develop their reasoning expertise. key chapters revised and updated nature of clinical reasoning sections have been expanded increase in emphasis on collaborative reasoning core model of clinical reasoning has been revised and updated |
| artificial intelligence in nursing education: Artificial Intelligence Applications Using ChatGPT in Education: Case Studies and Practices Aslam, Muhammad Shahzad, Nisar, Saima, 2023-08-29 In the realm of education, the challenge lies in effectively utilizing Artificial Intelligence to transform medical learning. Artificial Intelligence Applications Using ChatGPT in Education: Case Studies and Practices, authored by Muhammad Shahzad Aslam and Saima Nisar, offers insights into this issue. With expertise in Medical and Health Education, and Health Informatics, the authors explore AI's potential in reshaping medical education. Traditional medical education struggles to keep up with expanding knowledge and evolving medical science, leaving educators and students overwhelmed by vast information. Ethical concerns, such as plagiarism, further complicate matters. A solution is needed that blends technology with effective teaching. Artificial Intelligence Applications Using ChatGPT in Education: Case Studies and Practices proposes such a solution. By harnessing ChatGPT's capabilities as an AI chatbot, the book suggests a self-guided learning tool. Backed by case studies, the authors demonstrate how ChatGPT can become a personalized tutor, helping students grasp complex medical concepts at their own pace. The book also delves into the ethical aspects of AI integration, ensuring responsible use in academia. |
| artificial intelligence in nursing education: Artificial Intelligence and K-12 Education Joseph Mintz, Wayne Holmes, Leping Liu, Maria Perez-Ortiz, 2024-11-25 This book problematizes and explores appropriate ways of using AI technology that can augment educational practice, especially in K-12 teaching and learning. Since the launch of OpenAI ChatGPT in November 2022, people have been debating “to chat or to cheat” while more and more educators have started to explore “to add or to integrate” it into teaching and learning. A list of questions has been on the way. What can ChatGPT produce? How accurate can the contents produced by the GPT be? What are the considerations that an instructor should have when using AI technology for student learning? To what extent can ChatGPT compete with humans in terms of learning? ChatGPT is just a technology tool, but it drops a huge bomb in the field of education, and even changes the way many think about education. The contributors of this book, as well as probing the ethical conundrums presented by generative AI and other new technologies in AI&ED, summarize an overview of practice, provided first-hand experiences, and suggested strategies and methods that are workable in the field. This cutting-edge volume will be of interest to researchers, scholars and practitioners of education, education technology, sociology, ethics and artificial intelligence. It was originally published as a special issue of Computers in the Schools. |
| artificial intelligence in nursing education: Transcultural Artificial Intelligence and Robotics in Health and Social Care Irena Papadopoulos, Christina Koulouglioti, Chris Papadopoulos, Antonio Sgorbissa, 2022-04-22 Transcultural Artificial Intelligence and Robotics in Health and Social Care provides healthcare professionals with a deeper understanding of the incredible opportunities brought by the emerging field of AI robotics. In addition, it provides robotic researchers with the point-of-view of healthcare professionals to understand what the healthcare sector – as well as the market – really needs from robotics technology. By doing so, the book fills an important gap between both fields in order to leverage new developments and collaborative work in favor of global patients. The book is aimed at the non-technical reader, especially health and social care professionals, and explains in a simple way the technological principles applied in the development of socially assistive humanoid AI robots (SAHR), the values which guide such developments, the ethics related to them, and research approaches in the field, with a focus on achieving a culturally competent SAHR. - 2023 PROSE Awards - Winner: Category: Nursing and Allied Health: Association of American Publishers - Presents user-friendly and stage-by-stage information to help readers appreciate how AI robots work and how they can be integrated in their work environments - Explains why AI and socially assistive robotics need to be culturally competent - Helps reduce readers' fears and change negative prejudices they may have about robots as a relevant tool for healthcare - Written by experts in AI robotics and the creators of transcultural health/social robotics - Informed by the largest trial conducted with real patients |
| artificial intelligence in nursing education: Artificial Intelligence in Education Carolyn Penstein Rosé, Roberto Martínez-Maldonado, H. Ulrich Hoppe, Rose Luckin, Manolis Mavrikis, Kaska Porayska-Pomsta, Bruce McLaren, Benedict du Boulay, 2018-06-20 This two volume set LNAI 10947 and LNAI 10948 constitutes the proceedings of the 19th International Conference on Artificial Intelligence in Education, AIED 2018, held in London, UK, in June 2018.The 45 full papers presented in this book together with 76 poster papers, 11 young researchers tracks, 14 industry papers and 10 workshop papers were carefully reviewed and selected from 192 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas. |
| artificial intelligence in nursing education: Perspectives in Ambulatory Care Nursing Caroline Coburn, Deena Gilland, Beth Ann Swan, 2021-01-15 The perfect ambulatory care primer for undergraduate nursing students or practicing nurses transitioning from acute care settings, Perspectives in Ambulatory Care delivers expert insight into this evolving specialty and familiarizes readers with the top issues and trends they’ll encounter in ambulatory nursing practice. This authoritative resource clarifies the distinctions between ambulatory care and acute care, details the wide variety of ambulatory care roles and settings and demonstrates the growing impact and importance of nurses outside the hospital setting to help readers confidently meet the challenges of a changing healthcare landscape and succeed in this critical area of care. |
| artificial intelligence in nursing education: Clinical Simulations in Nursing Education Pamela Jeffries, 2022-09-21 In today’s quickly changing healthcare environment, simulation has become an indispensable strategy for preparing nursing students to deliver optimal patient care. Clinical Simulations in Nursing Education: Advanced Concepts, Trends, and Opportunities, Second Edition, takes the use of simulations to the next level, exploring innovative teaching/learning methods, new clinical models, and up-to-date best practices for providing high-quality education. From the evolution of clinical simulations to the use of more virtual simulations, incorporation of important constructs such as the social determinants of health, and the use of simulations in nursing education and competency-based testing, this engaging resource continues to provide intermediate and advanced simulation users and advocates with critical considerations for advancing simulation in nursing education. The comprehensive updated second edition focuses on the latest trends and concepts in simulation pedagogy to help nurse educators confidently prepare for their role in developing, planning, implementing, evaluating, and conducting research for effective simulation programs. |
| artificial intelligence in nursing education: Introduction to Nursing Informatics Kathryn J. Hannah, Marion J. Ball, Margaret J.A. Edwards, 2013-04-17 This series is intended for the rapidly increasing number of health care professionals who have rudimentary knowledge and experience in health care computing and are seeking opportunities to expand their horizons. It does not attempt to compete with the primers already on the market. Eminent international experts will edit, author, or contribute to each volume in order to provide comprehensive and current accounts of in novations and future trends in this quickly evolving field. Each book will be practical, easy to use, and weIl referenced. Our aim is for the series to encompass all of the health professions by focusing on specific professions, such as nursing, in individual volumes. However, integrated computing systems are only one tool for improving communication among members of the health care team. Therefore, it is our hope that the series will stimulate professionals to explore additional me ans of fostering interdisciplinary exchange. This se ries springs from a professional collaboration that has grown over the years into a highly valued personal friendship. Our joint values put people first. If the Computers in Health Care series lets us share those values by helping health care professionals to communicate their ideas for the benefit of patients, then our efforts will have succeeded. |
| artificial intelligence in nursing education: Book Only Dee McGonigle, Kathleen Mastrian, 2012 This book is the ideal student guide to the history of healthcare informatics, current issues, basic informatics concepts, and health information management applications. |
| artificial intelligence in nursing education: Oxford Handbook of Ethics of AI Markus D. Dubber, Frank Pasquale, Sunit Das, 2020-06-30 This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term A.I. is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether human or A.I. |
| artificial intelligence in nursing education: AI in Learning: Designing the Future Hannele Niemi, Roy D. Pea, Yu Lu, 2022-11-26 AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it. Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This open access book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning. This book will be of use to a variety of readers, including researchers, AI users, companies and policy makers. |
| artificial intelligence in nursing education: Artificial Intelligence in Education Wayne Holmes, Maya Bialik, Charles Fadel, 2019-02-28 The landscape for education has been rapidly changing in the last years: demographic changes affecting the makeup of families, multiple school options available to children, wealth disparities, the global economy demanding new skills from workers, and continued breakthroughs in technology are some of the factors impacting education. Given these changes, how can schools continue to prepare students for the future? In a world where information is readily available online, how can schools continue to be relevant? The emergence of Artificial Intelligence (AI) has exacerbated the need to have these conversations. Its impact on education and the multiple possibilities that it offers are putting pressure on educational leaders to reformulate the school curriculum and the channels to deliver it. The book Artificial Intelligence in Education, Promises and Implications for Teaching and Learning by the Center for Curriculum Redesign immerses the reader in a discussion on what to teach students in the era of AI and examines how AI is already demanding much needed updates to the school curriculum, including modernizing its content, focusing on core concepts, and embedding interdisciplinary themes and competencies with the end goal of making learning more enjoyable and useful in students' lives. The second part of the book dives into the history of AI in education, its techniques and applications -including the way AI can help teachers be more effective, and finishes on a reflection about the social aspects of AI. This book is a must-read for educators and policy-makers who want to prepare schools to face the uncertainties of the future and keep them relevant. --Amada Torres, VP, Studies, Insights, and Research, National Association of Independent School (NAIS) The rapid advances in technology in recent decades have already brought about substantial changes in education, opening up new opportunities to teach and learn anywhere anytime and providing new tools and methods to improve learning outcomes and support innovative teaching and learning.Research into artificial intelligence and machine learning in education goes back to the late 1970s. Artificial intelligence methods were generally employed in two ways: to design and facilitate interactive learning environments that would support learning by doing, and to design and implement tutoring systems by adapting instructions with respect to the students' knowledge state.But this is just the beginning. As Artificial Intelligence in Education shows, AI is increasingly used in education and learning contexts. The collision of three areas - data, computation and education - is set to have far-reaching consequences, raising fundamental questions about the nature of education: what is taught and how it is taught. Artificial Intelligence in Education is an important, if at times disturbing, contribution to the debate on AI and provides a detailed analysis on how it may affect the way teachers and students engage in education. The book describes how artificial intelligence may impact on curriculum design, on the individualisation of learning, and on assessment, offering some tantalising glimpses into the future (the end of exams, your very own lifelong learning companion) while not falling victim to tech-hype. The enormous ethical, technical and pedagogical challenges ahead are spelt out, and there is a real risk that the rapid advances in artificial intelligence products and services will outstrip education systems' capacity to understand, manage and integrate them appropriately. As the book concludes: We can either leave it to others (the computer scientists, AI engineers and big tech companies) to decide how artificial intelligence in education unfolds, or we can engage in productive dialogue.I commend this book to anyone concerned with the future of education in a digital world. --Marc Durando, Executive Director, European Schoolnet |
| artificial intelligence in nursing education: Artificial Intelligence in the Field of Health Dr. Shahul Hameed Pakkir Mohamed, Dr. Mathar Mohideen Nagoor Thangam, Mr. Arup Das, Dr. Keshamma E., 2022-07-08 Artificial Intelligence (AI) and related propels are logically dominating in business and society, and are beginning to be applied to clinical benefits. These advancements might perhaps change various pieces of patient thought, as well as administrative cycles inside the provider, payer, and medication affiliations. There are currently different investigation studies recommending that AI can continue as well as or better than individuals at key clinical benefits tasks, such as diagnosing disease. Today, estimations are at this point beating radiologists at spotting perilous developments and guiding experts in how to fabricate associates for costly clinical starters. In any case, in light of multiple factors, we acknowledge that it will be various earlier years AI replaces individuals for far-reaching clinical cycle regions. In this article, we depict both the potential that AI offers to robotize parts of care and a piece of the blocks too fast execution of AI in clinical benefits. |
| artificial intelligence in nursing education: Deep Medicine Eric Topol, 2019-03-12 A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved. |
| artificial intelligence in nursing education: Artificial Intelligence and Big Data Analytics for Smart Healthcare Miltiadis Lytras, Akila Sarirete, Anna Visvizi, Kwok Tai Chui, 2021-10-22 Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. - Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine - Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them - Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers |
| artificial intelligence in nursing education: Impact of AI Technologies on Teaching, Learning, and Research in Higher Education Verma, Shivani, Tomar, Pradeep, 2020-08-21 Within higher education, there are enormous untapped opportunities for product/services companies, administrators, educators, start-ups. and technology professionals to begin embracing artificial intelligence (AI) across the student ecosystem and infuse innovation into traditional academic processes by leveraging disruptive technologies. This type of human-machine interface presents the immediate potential to change the way we learn, memorize, access, and create information. These solutions present new openings for education for all while fostering lifelong learning in a strengthened model that can preserve the integrity of core values and the purpose of higher education. Impact of AI Technologies on Teaching, Learning, and Research in Higher Education explores the phenomena of the emergence of the use of AI in teaching and learning in higher education, including examining the positive and negative aspects of AI. Recent technological advancements and the increasing speed of adopting new technologies in higher education are discussed in order to predict the future nature of higher education in a world where AI is part of the fabric of universities. The book also investigates educational implications of emerging technologies on the way students learn and how institutions teach and evolve. Finally, challenges for the adoption of these technologies for teaching, learning, student support, and administration are addressed. Highlighting such tools as machine learning, natural language processing, and self-learning systems, this scholarly book is of interest to university administrators, educational software developers, instructional designers, policymakers, government officials, academicians, researchers, and students, as well as international agencies, organizations, and professionals interested in implementing AI in higher education. |
| artificial intelligence in nursing education: Developing Online Courses in Nursing Education, Fourth Edition Carol O'Neil, PhD, RN, CNE, Cheryl Fisher, EdD, RN-BC, Matthew Rietschel, MS, 2019-06-21 Addresses importance of new technology and changing structures of online learning This authoritative text shows nurse educators and students how to teach in the online environment, using best practices and the latest technology. The fourth edition discusses the importance of lifelong learning and the relationship to flexible online learning environments, which are changing the dynamics of education. This valuable resource provides updated strategies for organizing and disseminating course content and examines such topics as massive open online courses (MOOCs), certificates, badges, and stackable degrees. The fourth edition also provides the latest evidence-based research examining student–teacher interactions, course management, web-based resources, and best practices. Chapters include real-world examples and applications of these concepts. New to the Fourth Edition: Delivers four new chapters on the changing role of the nurse educator, changing faculty roles, designing flexible learning environments, and using technology to meet the needs of students Addresses the interaction between nurse educators and instructional designers Provides enhanced understanding of design, design strategies, and technology Includes updated best practices for pedagogy, interaction, reconceptualizing course content, student assessment, course evaluation, and more Underscores the importance of lifelong learning and flexible, creative learning environments Key Features: Demonstrates foundational concepts for using technology to teach online Delineates pathways for using online modalities to engineer learning Delivers theories and frameworks guiding the development and use of a flexible environment Identifies guiding structures for maximizing learning in online environments Defines the distinct role of the online educator Promotes best use of technology according to the needs of the learner Includes abundant examples and reflective questions Supplemental instructor’s manual included |
| artificial intelligence in nursing education: Informatics and Nursing Jeanne Sewell, 2018-09-06 Publisher's Note: Products purchased from 3rd Party sellers are not guaranteed by the Publisher for quality, authenticity, or access to any online entitlements included with the product. Focusing on the information every nurse should know and capturing cutting-edge advances in a rapidly changing field, this practical text helps students build the communication and information literacy skills they need to integrate informatics into practice. This edition retains the key coverage of the previous edition, including office cloud computing software, interoperability, consumer informatics, telehealth, clinical information systems, social media use guidelines, and software and hardware developments, while offering new information and references throughout. Highlights of the 6th Edition Updated coverage Built-in learning aids Integrated QSEN scenarios Available with CoursePoint for Informatics and Nursing, 6th Edition Combining the world-class content of this text with Lippincott’s innovative learning tools in one easy-to-use digital environment, Lippincott CoursePoint transforms the teaching and learning experience, making the full spectrum of nursing education more approachable than ever for you and your students. This powerful solution is designed for the way students learn, providing didactic content in the context of real-life scenarios—at the exact moments when students are connecting theory to application. Features Create an active learning environment that engages students of various learning styles. Deliver a diverse array of content types—interactive learning modules, quizzes, and more—designed for today's interactive learners. Address core concepts while inspiring critical thinking. Reinforce understanding with instant SmartSense remediation links that connect students to the exact content they need at the precise moment they need it. Analyze results and adapt teaching methods to better meet individual students’ strengths and weaknesses. Empower students to learn at their own pace in an online environment available anytime, anywhere. |
| artificial intelligence in nursing education: Bridging Human Intelligence and Artificial Intelligence Mark V. Albert, Lin Lin, Michael J. Spector, Lemoyne S. Dunn, 2022-02-24 This edited volume is based on contributions from the TCET-AECT “Human-Technology Frontier: Understanding the Learning of Now to Prepare for the Work of the Future Symposium” held in Denton, Texas on May 16-18, sponsored by AECT. The authors embrace an integrative approach to designing and implementing advances technologies in learning and instruction, and focus on the emerging themes of artificial intelligence, human-computer interactions, and the resulting instructional design. The volume will be divided into four parts: (1) Trends and future in learning and learning technologies expected in the next 10 years; (2) Technologies likely to have a significant impact on learning in the next 10 years; (3) Challenges that will need to be addressed and resolved in order to achieve significant and sustained improvement in learning; and (4) Reflections and insights from the Symposium that should be pursued and that can form the basis for productive research collaborations. The primary audience for this volume is academics and researchers in disciplines such as artificial intelligence, cognitive science, computer science, educational psychology, instructional design, human-computer interactions, information science, library science, and technology integration. |
| artificial intelligence in nursing education: Teaching Tomorrow's Nurses Jennifer O'Rourke, Andrew Bobal, 2024-06-27 Teaching Tomorrow’s Nurses: A Technology-Enhanced Approach is your field guide to optimal learning outcomes through technology. Packed with expert perspectives from across the nursing education spectrum, this comprehensive toolkit walks you through the why and how of using technology to engage and evaluate learners, empowering you to make informed choices and confidently implement them in your course. Embrace your potential and ensure student success with: Detailed descriptions of traditional and emerging technologies relevant to nursing academia;Evidence-based advantages and challenges for each tool; Straightforward evaluation protocols and approaches; Sample cases that guide you through course integration for in-person and virtual learning models;Real-world examples mapped to learning objectives |
| artificial intelligence in nursing education: Innovative Teaching Strategies in Nursing and Related Health Professions Debra Hagler, Beth L Hultquist, Martha J Bradshaw, 2024-10 The recent pandemic has driven rapid change in educational technology use, while the post-pandemic phase has driven a desire for intentional social learning and interaction. Revisions will reframe teaching strategies and introduce additional methods to support these developments. Key Revision Changes: Major changes include emphasis and new content on diversity and inclusion, clinical judgment, competency-based education, and virtual/augmented reality. Authors are to provide a crosswalk of product's solution to the competencies and outcomes expected. The most pertinent competencies for users of this text are the NLN Core Competencies of Academic Nurse Educators (2005)-- |
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something natural : man-made. …
ARTIFICIAL | English meaning - Cambridge Dictionary
ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by people, often…. Learn …
Artificial - definition of artificial by The Free Dictionary
1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a natural product, esp as a …
ARTIFICIAL Definition & Meaning | Dictionary.com
Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is often used …
ARTIFICIAL definition and meaning | Collins English Dictionary
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for example using science or …
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something …
ARTIFICIAL | English meaning - Cambridge Dictionary
ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by …
Artificial - definition of artificial by The Free Dictiona…
1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a …
ARTIFICIAL Definition & Meaning | Dictionary.com
Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is …
ARTIFICIAL definition and meaning | Collins English Dict…
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for …
