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Author: B. Séroussi Publisher: IOS Press ISBN: 1643682857 Category : Medical Languages : en Pages : 1018
Book Description
Artificial Intelligence (AI) in healthcare promises to improve the accuracy of diagnosis and screening, support clinical care, and assist in various public health interventions such as disease surveillance, outbreak response, and health system management. But the increasing importance of AI in healthcare means that trustworthy AI is vital to achieve the beneficial impacts on health anticipated by both health professionals and patients. This book presents the proceedings of the 32nd Medical Informatics Europe Conference (MIE2022), organized by the European Federation for Medical Informatics (EFMI) and held from 27 - 30 May 2022 in Nice, France. The theme of the conference was Challenges of Trustable AI and Added-Value on Health. Over 400 submissions were received from 43 countries, and were reviewed in a thorough process by at least three reviewers before being assessed by an SPC co-chair, with papers requiring major revision undergoing further review. Included here are 147 full papers (acceptance rate 54%), 23 short papers and 79 posters from the conference. Topics covered include the usual sub-domains of biomedical informatics: decision support and clinical information systems; clinical research informatics; knowledge management and representation; consumer health informatics; natural language processing; public health informatics; and privacy, ethical and societal aspects, but also innovative approaches to the collection, such as organization and analysis of data and knowledge related to health and wellbeing, as well as theoretical and applied contributions to AI methods and algorithms. Providing an overview of the latest developments in medical informatics, the book will be of interest to all those involved in the development and provision of healthcare today.
Author: B. Séroussi Publisher: IOS Press ISBN: 1643682857 Category : Medical Languages : en Pages : 1018
Book Description
Artificial Intelligence (AI) in healthcare promises to improve the accuracy of diagnosis and screening, support clinical care, and assist in various public health interventions such as disease surveillance, outbreak response, and health system management. But the increasing importance of AI in healthcare means that trustworthy AI is vital to achieve the beneficial impacts on health anticipated by both health professionals and patients. This book presents the proceedings of the 32nd Medical Informatics Europe Conference (MIE2022), organized by the European Federation for Medical Informatics (EFMI) and held from 27 - 30 May 2022 in Nice, France. The theme of the conference was Challenges of Trustable AI and Added-Value on Health. Over 400 submissions were received from 43 countries, and were reviewed in a thorough process by at least three reviewers before being assessed by an SPC co-chair, with papers requiring major revision undergoing further review. Included here are 147 full papers (acceptance rate 54%), 23 short papers and 79 posters from the conference. Topics covered include the usual sub-domains of biomedical informatics: decision support and clinical information systems; clinical research informatics; knowledge management and representation; consumer health informatics; natural language processing; public health informatics; and privacy, ethical and societal aspects, but also innovative approaches to the collection, such as organization and analysis of data and knowledge related to health and wellbeing, as well as theoretical and applied contributions to AI methods and algorithms. Providing an overview of the latest developments in medical informatics, the book will be of interest to all those involved in the development and provision of healthcare today.
Author: B. Séroussi Publisher: ISBN: 9781643682846 Category : Languages : en Pages : 0
Book Description
Artificial Intelligence (AI) in healthcare promises to improve the accuracy of diagnosis and screening, support clinical care, and assist in various public health interventions such as disease surveillance, outbreak response, and health system management. But the increasing importance of AI in healthcare means that trustworthy AI is vital to achieve the beneficial impacts on health anticipated by both health professionals and patients.This book presents the proceedings of the 32nd Medical Informatics Europe Conference (MIE2022), organized by the European Federation for Medical Informatics (EFMI) and held from 27 - 30 May 2022 in Nice, France. The theme of the conference was Challenges of Trustable AI and Added-Value on Health. Over 400 submissions were received from 43 countries, and were reviewed in a thorough process by at least three reviewers before being assessed by an SPC co-chair, with papers requiring major revision undergoing further review. Included here are 147 full papers (acceptance rate 54%), 23 short papers and 79 posters from the conference. Topics covered include the usual sub-domains of biomedical informatics: decision support and clinical information systems; clinical research informatics; knowledge management and representation; consumer health informatics; natural language processing; public health informatics; and privacy, ethical and societal aspects, but also innovative approaches to the collection, such as organization and analysis of data and knowledge related to health and wellbeing, as well as theoretical and applied contributions to AI methods and algorithms. Providing an overview of the latest developments in medical informatics, the book will be of interest to all those involved in the development and provision of healthcare today.
Author: Adam Bohr Publisher: Academic Press ISBN: 0128184396 Category : Computers Languages : en Pages : 385
Book Description
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: OECD Publisher: OECD Publishing ISBN: 9264545190 Category : Languages : en Pages : 152
Book Description
The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises.
Author: David Riaño Publisher: Springer ISBN: 303021642X Category : Computers Languages : en Pages : 431
Book Description
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: Leo Anthony Celi Publisher: Springer Nature ISBN: 3030479943 Category : Medical Languages : en Pages : 471
Book Description
This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.
Author: Kerrie L. Holley Publisher: "O'Reilly Media, Inc." ISBN: 149206310X Category : Computers Languages : en Pages : 222
Book Description
AI is poised to transform every aspect of healthcare, including the way we manage personal health, from customer experience and clinical care to healthcare cost reductions. This practical book is one of the first to describe present and future use cases where AI can help solve pernicious healthcare problems. Kerrie Holley and Siupo Becker provide guidance to help informatics and healthcare leadership create AI strategy and implementation plans for healthcare. With this book, business stakeholders and practitioners will be able to build knowledge, a roadmap, and the confidence to support AIin their organizations—without getting into the weeds of algorithms or open source frameworks. Cowritten by an AI technologist and a medical doctor who leverages AI to solve healthcare’s most difficult challenges, this book covers: The myths and realities of AI, now and in the future Human-centered AI: what it is and how to make it possible Using various AI technologies to go beyond precision medicine How to deliver patient care using the IoT and ambient computing with AI How AI can help reduce waste in healthcare AI strategy and how to identify high-priority AI application
Author: Alessandro Crimi Publisher: Springer ISBN: 3319555243 Category : Computers Languages : en Pages : 297
Book Description
This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Brain Lesion, as well as the challenges on Brain Tumor Segmentation (BRATS), Ischemic Stroke Lesion Image Segmentation (ISLES), and the Mild Traumatic Brain Injury Outcome Prediction (mTOP), held in Athens, October 17, 2016, in conjunction with the International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016. The 26 papers presented in this volume were carefully reviewed. They present the latest advances in segmentation, disease prognosis and other applications to the clinical context.
Author: David C. Klonoff Publisher: Elsevier ISBN: 0128174862 Category : Medical Languages : en Pages : 311
Book Description
Diabetes Digital Health brings together the multifaceted information surrounding the science of digital health from an academic, regulatory, industrial, investment and cybersecurity perspective. Clinicians and researchers who are developing and evaluating mobile apps for diabetes patients will find this essential reading, as will industry people whose companies are developing mobile apps and sensors. - Provides valuable information for clinicians, researchers and industry about the design and evaluation of patient-facing diabetes adherence technologies - Highlights cutting-edge topics that are presented and discussed at the Digital Diabetes Congress
Author: Beena Ammanath Publisher: John Wiley & Sons ISBN: 1119867959 Category : Computers Languages : en Pages : 230
Book Description
An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI.
Author: B. Séroussi
Author: B. Séroussi
Author: B. Séroussi
Author: Adam Bohr
Author: OECD
Author: David Riaño
Author: Leo Anthony Celi
Author: Kerrie L. Holley
Author: Alessandro Crimi
Author: David C. Klonoff
Author: Beena Ammanath