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| Author | : Gabriele Werner-Felmayer |
| Publisher | : Frontiers Media SA |
| Total Pages | : 115 |
| Release | : 2023-10-06 |
| Genre | : Science |
| ISBN | : 2832535348 |
| Author | : David Riaño |
| Publisher | : Springer |
| Total Pages | : 431 |
| Release | : 2019-06-19 |
| Genre | : Computers |
| ISBN | : 303021642X |
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.
| Author | : Adam Bohr |
| Publisher | : Academic Press |
| Total Pages | : 385 |
| Release | : 2020-06-21 |
| Genre | : Computers |
| ISBN | : 0128184396 |
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
| Author | : Joseph JY Sung |
| Publisher | : Elsevier |
| Total Pages | : 162 |
| Release | : 2024-03-29 |
| Genre | : Science |
| ISBN | : 0323950698 |
Although AI is opening new and exciting opportunities in healthcare, implementation still faces challenges. Artificial Intelligence in Medicine: From Ethical, Social, and Legal Perspectives provides answers on how to improve acceptance and diminish the anxiety of the use of AI-assisted medicine. Through a series of social, ethical, and legal discussions from clinicians, social scientists, ethicists, and legal experts this important reference has coverage that includes good data custodianship and stewardship; data access, data bias, data & healthcare equity; privacy and confidentiality; algorithmic understanding; and regulatory guidance, accountability, and legal responsibility. This reference will explain to healthcare providers how AI will enhance healthcare, will introduce to scientists and researchers the ethical and social aspect of AI that needs to be addressed, and will urge policymakers and health authorities to consider the legal framework needed to implement AI technology in healthcare. Discusses the issues that must be addressed to improve acceptance and diminish the anxiety and lack of trust surrounding the care of human health by machines Examines the delicate issues surrounding the use of AI in making life-and-death decisions Sets the framework of social, ethical, and legal aspects of healthcare for the future
| Author | : Giovanni Rubeis |
| Publisher | : Springer Nature |
| Total Pages | : 258 |
| Release | : |
| Genre | : |
| ISBN | : 3031557441 |
| Author | : Natasha H. Williams |
| Publisher | : Springer Nature |
| Total Pages | : 121 |
| Release | : 2024-01-01 |
| Genre | : Philosophy |
| ISBN | : 303148262X |
This book explores the ethical problems of algorithmic bias and its potential impact on populations that experience health disparities by examining the historical underpinnings of explicit and implicit bias, the influence of the social determinants of health, and the inclusion of racial and ethnic minorities in data. Over the last twenty-five years, the diagnosis and treatment of disease have advanced at breakneck speeds. Currently, we have technologies that have revolutionized the practice of medicine, such as telemedicine, precision medicine, big data, and AI. These technologies, especially AI, promise to improve the quality of patient care, lower health care costs, improve patient treatment outcomes, and decrease patient mortality. AI may also be a tool that reduces health disparities; however, algorithmic bias may impede its success. This book explores the risks of using AI in the context of health disparities. It is of interest to health services researchers, ethicists, policy analysts, social scientists, health disparities researchers, and AI policy makers.
| Author | : VIRUTI SHIVAN |
| Publisher | : Viruti Satyan Shivan |
| Total Pages | : 226 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
In the rapidly evolving world of healthcare, Artificial Intelligence (AI) stands at the forefront, heralding a new era of precision, efficiency, and patient-centric care. "Artificial Intelligence Healthcare Analyst - The Comprehensive Guide" offers an unprecedented journey into the heart of this transformation, equipping professionals, enthusiasts, and newcomers with the knowledge to navigate, innovate, and excel in this dynamic field. Without relying on images or illustrations for clarity, this guide transcends the conventional, offering a deeply engaging and insightful exploration into how AI technologies are reshaping healthcare analytics, decision-making processes, and patient outcomes. Through vivid hypothetical scenarios and personal anecdotes from industry insiders, readers will discover the untapped potential of AI in healthcare, understanding its implications, ethical considerations, and the pathway to becoming proficient AI healthcare analysts. Dive into a world where data becomes a beacon of hope, and algorithms the architects of a healthier future. This book is more than just a guide; it's an invitation to be part of a revolution that promises to redefine healthcare delivery. As we peel back the layers of complexity surrounding AI applications in healthcare, readers will gain not only a comprehensive understanding of the tools and technologies but also an appreciation for the profound impact AI can have on human health. Without the need for images, the narrative is rich with examples and theoretical discussions that bring the subject to life, making "Artificial Intelligence Healthcare Analyst - The Comprehensive Guide" an essential resource for anyone looking to make a meaningful impact in the healthcare industry through the power of AI.
| Author | : Simon Peter van Rysewyk |
| Publisher | : Springer |
| Total Pages | : 371 |
| Release | : 2014-09-05 |
| Genre | : Technology & Engineering |
| ISBN | : 331908108X |
The essays in this book, written by researchers from both humanities and science, describe various theoretical and experimental approaches to adding medical ethics to a machine, what design features are necessary in order to achieve this, philosophical and practical questions concerning justice, rights, decision-making and responsibility in medical contexts, and accurately modeling essential physician-machine-patient relationships. In medical settings, machines are in close proximity with human beings: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old and with medical professionals. Machines in these contexts are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for empathy and emotion detection necessary? What about consciousness? This collection is the first book that addresses these 21st-century concerns.
| Author | : Kumar, Rajeev |
| Publisher | : IGI Global |
| Total Pages | : 475 |
| Release | : 2024-03-04 |
| Genre | : Computers |
| ISBN | : |
In the advancing fields of artificial intelligence (AI) and data science, a pressing ethical dilemma arises. As technology continues its relentless march forward, ethical considerations within these domains become increasingly complex and critical. Bias in algorithms, lack of transparency, data privacy breaches, and the broader societal repercussions of AI applications are demanding urgent attention. This ethical quandary poses a formidable challenge for researchers, academics, and industry professionals alike, threatening the very foundation of responsible technological innovation. Navigating this ethical minefield requires a comprehensive understanding of the multifaceted issues at hand. The Ethical Frontier of AI and Data Analysis is an indispensable resource crafted to address the ethical challenges that define the future of AI and data science. Researchers and academics who find themselves at the forefront of this challenge are grappling with the evolving landscape of AI and data science ethics. Underscoring the need for this book is the current lack of clarity on ethical frameworks, bias mitigation strategies, and the broader societal implications, which hinder progress and leave a void in the discourse. As the demand for responsible AI solutions intensifies, the imperative for this reliable guide that consolidates, explores, and advances the dialogue on ethical considerations grows exponentially.
| Author | : Tina Nguyen |
| Publisher | : Ethics International Press |
| Total Pages | : 229 |
| Release | : 2023-11-25 |
| Genre | : Medical |
| ISBN | : 180441106X |
This book explores the ethical governance of Artificial Intelligence (AI) & Machine Learning (ML) in healthcare. AI/ML usage in healthcare as well as our daily lives is not new. However, the direct, and oftentimes long-term effects of current technologies, in addition to the onset of future innovations, have caused much debate about the safety of AI/ML. On the one hand, AI/ML has the potential to provide effective and efficient care to patients, and this sways the argument in favor of continuing to use AI/ML; but on the other hand, the dangers (including unforeseen future consequences of the further development of the technology) leads to vehement disagreement with further AI/ML usage. Due to its potential for beneficial outcomes, the book opts to push for ethical AI/ML to be developed and examines various areas in healthcare, such as big data analytics and clinical decision-making, to uncover and discuss the importance of developing ethical governance for AI/ML in this setting.
