[PDF] The Ethics Of Biomedical Big Data eBook

Author : Brent Daniel Mittelstadt
Publisher : Springer
Page : 478 pages
File Size : 42,22 MB
Release : 2016-08-03
Category : Philosophy
ISBN : 3319335251

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This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward.

Author : Annika Richterich
Publisher : University of Westminster Press
Page : 156 pages
File Size : 45,85 MB
Release : 2018-04-13
Category : Social Science
ISBN : 1911534734

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This book highlights that the capacity for gathering, analysing, and utilising vast amounts of digital (user) data raises significant ethical issues. Annika Richterich provides a systematic contemporary overview of the field of critical data studies that reflects on practices of digital data collection and analysis. The book assesses in detail one big data research area: biomedical studies, focused on epidemiological surveillance. Specific case studies explore how big data have been used in academic work. The Big Data Agenda concludes that the use of big data in research urgently needs to be considered from the vantage point of ethics and social justice. Drawing upon discourse ethics and critical data studies, Richterich argues that entanglements between big data research and technology/ internet corporations have emerged. In consequence, more opportunities for discussing and negotiating emerging research practices and their implications for societal values are needed.

Author : I. Glenn Cohen
Publisher : Cambridge University Press
Page : 374 pages
File Size : 44,96 MB
Release : 2018-03-08
Category : Law
ISBN : 110815364X

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When data from all aspects of our lives can be relevant to our health - from our habits at the grocery store and our Google searches to our FitBit data and our medical records - can we really differentiate between big data and health big data? Will health big data be used for good, such as to improve drug safety, or ill, as in insurance discrimination? Will it disrupt health care (and the health care system) as we know it? Will it be possible to protect our health privacy? What barriers will there be to collecting and utilizing health big data? What role should law play, and what ethical concerns may arise? This timely, groundbreaking volume explores these questions and more from a variety of perspectives, examining how law promotes or discourages the use of big data in the health care sphere, and also what we can learn from other sectors.

Author : Markus Dirk Dubber
Publisher : Oxford Handbooks
Page : 896 pages
File Size : 33,95 MB
Release : 2020
Category : Business & Economics
ISBN : 019006739X

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This interdisciplinary and international handbook captures and shapes much needed reflection on normative frameworks for the production, application, and use of artificial intelligence in all spheres of individual, commercial, social, and public life.

Author : Jenny Krutzinna
Publisher : Springer
Page : 198 pages
File Size : 10,80 MB
Release : 2019-01-16
Category : Medical
ISBN : 3030043630

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This open access book presents an ethical approach to utilizing personal medical data. It features essays that combine academic argument with practical application of ethical principles. The contributors are experts in ethics and law. They address the challenges in the re-use of medical data of the deceased on a voluntary basis. This pioneering study looks at the many factors involved when individuals and organizations wish to share information for research, policy-making, and humanitarian purposes. Today, it is easy to donate blood or even organs, but it is virtually impossible to donate one’s own medical data. This is seen as ethically unacceptable. Yet, data donation can greatly benefit the welfare of our societies. This collection provides timely interdisciplinary research on biomedical big data. Topics include the ethics of data donation, the legal and regulatory challenges, and the current and future collaborations. Readers will learn about the ethical and regulatory challenges associated with medical data donations. They will also better understand the special nature of using deceased data for research purposes with regard to ethical principles of autonomy, beneficence, and justice. In addition, the contributors identify the key governance issues of such a scheme. The essays also look at what we can learn in terms of best practice from existing medical data schemes.

Author : Geoffrey S. Ginsburg
Publisher : Academic Press
Page : 379 pages
File Size : 43,11 MB
Release : 2022-04-09
Category : Science
ISBN : 0128006536

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Genomic and Precision Medicine: Oncology, Third Edition focuses on the applications of genome discovery as research points to personalized cancer therapies. Each chapter is organized to cover the application of genomics and personalized medicine tools and technologies to a) Risk Assessment and Susceptibility, b) Diagnosis and Prognosis, c) Pharmacogenomics and Precision Therapeutics, and d) Emerging and Future Opportunities in the field. Provides a comprehensive volume written and edited by oncology genomic specialists for oncology health providers Includes succinct commentary and key learning points that will assist providers with their local needs for implementation of genomic and personalized medicine into practice Presents an up-to-date overview on major opportunities for genomic and personalized medicine in practice Covers case studies that highlight the practical use of genomics in the management of patients

Author : Linnet Taylor
Publisher : Springer
Page : 249 pages
File Size : 34,24 MB
Release : 2016-12-28
Category : Philosophy
ISBN : 3319466089

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The goal of the book is to present the latest research on the new challenges of data technologies. It will offer an overview of the social, ethical and legal problems posed by group profiling, big data and predictive analysis and of the different approaches and methods that can be used to address them. In doing so, it will help the reader to gain a better grasp of the ethical and legal conundrums posed by group profiling. The volume first maps the current and emerging uses of new data technologies and clarifies the promises and dangers of group profiling in real life situations. It then balances this with an analysis of how far the current legal paradigm grants group rights to privacy and data protection, and discusses possible routes to addressing these problems. Finally, an afterword gathers the conclusions reached by the different authors and discuss future perspectives on regulating new data technologies.

Author : Anna C. Mastroianni
Publisher : Oxford University Press
Page : 992 pages
File Size : 17,30 MB
Release : 2019-07-23
Category : Medical
ISBN : 0190245212

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Natural disasters and cholera outbreaks. Ebola, SARS, and concerns over pandemic flu. HIV and AIDS. E. coli outbreaks from contaminated produce and fast foods. Threats of bioterrorism. Contamination of compounded drugs. Vaccination refusals and outbreaks of preventable diseases. These are just some of the headlines from the last 30-plus years highlighting the essential roles and responsibilities of public health, all of which come with ethical issues and the responsibilities they create. Public health has achieved extraordinary successes. And yet these successes also bring with them ethical tension. Not all public health successes are equally distributed in the population; extraordinary health disparities between rich and poor still exist. The most successful public health programs sometimes rely on policies that, while improving public health conditions, also limit individual rights. Public health practitioners and policymakers face these and other questions of ethics routinely in their work, and they must navigate their sometimes competing responsibilities to the health of the public with other important societal values such as privacy, autonomy, and prevailing cultural norms. This Oxford Handbook provides a sweeping and comprehensive review of the current state of public health ethics, addressing these and numerous other questions. Taking account of the wide range of topics under the umbrella of public health and the ethical issues raised by them, this volume is organized into fifteen sections. It begins with two sections that discuss the conceptual foundations, ethical tensions, and ethical frameworks of and for public health and how public health does its work. The thirteen sections that follow examine the application of public health ethics considerations and approaches across a broad range of public health topics. While chapters are organized into topical sections, each chapter is designed to serve as a standalone contribution. The book includes 73 chapters covering many topics from varying perspectives, a recognition of the diversity of the issues that define public health ethics in the U.S. and globally. This Handbook is an authoritative and indispensable guide to the state of public health ethics today.

Author : Valentina Emilia Balas
Publisher : Academic Press
Page : 320 pages
File Size : 49,5 MB
Release : 2019-11-13
Category : Science
ISBN : 0128183195

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Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more

Author : Wolfgang Pietsch
Publisher : Cambridge University Press
Page : 75 pages
File Size : 39,16 MB
Release : 2021-02-18
Category : Science
ISBN : 9781108706698

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Big Data and methods for analyzing large data sets such as machine learning have in recent times deeply transformed scientific practice in many fields. However, an epistemological study of these novel tools is still largely lacking. After a conceptual analysis of the notion of data and a brief introduction into the methodological dichotomy between inductivism and hypothetico-deductivism, several controversial theses regarding big data approaches are discussed. These include, whether correlation replaces causation, whether the end of theory is in sight and whether big data approaches constitute entirely novel scientific methodology. In this Element, I defend an inductivist view of big data research and argue that the type of induction employed by the most successful big data algorithms is variational induction in the tradition of Mill's methods. Based on this insight, the before-mentioned epistemological issues can be systematically addressed.