Clinical Decision Support Systems


Book Description

Building on the success of the previous editions, this fully updated book once again brings together worldwide experts to illustrate the underlying science and day-to-day use of decision support systems in clinical and educational settings. Topics discussed include: -Mathematical Foundations of Decision Support Systems -Design and Implementation Issues -Ethical and Legal Issues in Decision Support -Clinical Trials of Information Interventions -Hospital-Based Decision Support -Real World Case Studies




Artificial Intelligence in Healthcare


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




Precision Medicine and Artificial Intelligence


Book Description

Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions Provides background, milestone and examples of precision medicine Outlines the paradigm shift towards precision medicine driven by value-based systems Discusses future applications of precision medicine research using AI Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine




Lightweight Digital Trust Architectures in the Internet of Medical Things (IoMT)


Book Description

In the field of healthcare technology, the Internet of Medical Things (IoMT) stands at the forefront of progress, revolutionizing patient care through advanced monitoring and treatment modalities. However, this digital transformation brings forth a new challenge— the vulnerability of sensitive medical data to cyber threats. Lightweight Digital Trust Architectures in the Internet of Medical Things (IoMT) examines ways to fortify IoMT against potential breaches through the exploration of these trust architectures. Delving deep into data privacy technologies, the book examines the implications of regulatory frameworks such as GDPR, HIPAA, and cybersecurity law. It assesses traditional security methods and considers innovative approaches, offering insights into certificate generation, digital identification, and the optimization of network protocols for secure data transmission.Lightweight Digital Trust Architectures in the Internet of Medical Things (IoMT) illuminates the path forward for IoMT security. Its objectives are multi-faceted: from unraveling the intricacies of the health chain to dissecting the role of lightweight cryptographic key agreement mechanisms in safeguarding medical data. The book grapples with the challenges and advantages of implementing compact cryptographic techniques in healthcare, particularly within the decentralized framework of IoMT. By exploring the potential of Federated Learning (FL) in bolstering privacy and improving healthcare outcomes, the book aims to equip researchers, healthcare professionals, and IT experts with valuable knowledge. Through real-world case studies, it endeavors to pave the way for a future where security and efficiency seamlessly integrate in IoMT.




Teaching Legal Education in the Digital Age


Book Description

Teaching Legal Education in the Digital Age explores how legal pedagogy and curriculum design should be modernised to ensure that law students have a realistic view of the future of the legal profession. Using future readiness and digital empowerment as central themes, chapters discuss the use of technology to enhance the design and delivery of the curriculum and argue the need for the curriculum to be developed to prepare students for the use of technology in the workplace. The volume draws together a range of contributions to consider the impact of digital pedagogies in legal education and propose how technology can be used in the law curriculum to enhance student learning in law schools and lead excellence in teaching. Throughout, the authors consider what it means to be future-ready and what we can do as law academics to facilitate the knowledge, skills and dispositions needed by future-ready graduates. Part of Routledge’s series on Legal Pedagogy, this book will be of great interest to academics, post-graduate students, teachers and researchers of law, as well as those with a wider interest in legal pedagogy or legal practice.




Artificial Intelligence in Medicine


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.




Beyond Transparency


Book Description

The rise of open data in the public sector has sparked innovation, driven efficiency, and fueled economic development. While still emerging, we are seeing evidence of the transformative potential of open data in shaping the future of our civic life, and the opportunity to use open data to reimagine the relationship between residents and government, especially at the local level. As we look ahead, what have we learned so far from open data in practice and how we can apply those lessons to realize a more promising future for America's cities and communities? Edited by Brett Goldstein, former Chief Data Officer for the City of Chicago, with Code for America, this book features essays from over twenty of the world's leading experts in a first-of-its-kind instructive anthology about how open data is changing the face of our public institutions. Contributors include: Michael Flowers, Chief Analytics Officer, New York City Beth Blauer, former director of Maryland StateStat Jonathan Feldman, CIO, City of Asheville Tim O'Reilly, founder & CEO, O'Reilly Media Eric Gordon, Director of Engagement Game Lab, Emerson College Beth Niblock, CIO, Louisville Metro Government Ryan & Mike Alfred, Co-Founders, Brightscope Emer Coleman, former director of the London Datastore Mark Headd, Chief Data Officer, City of Philadelphia "As an essential volume for anyone interested in the future of governance, urban policy, design, data-driven policymaking, journalism, or civic engagement, "Beyond Transparency" combines the inspirational glow and political grit of Profiles in Courage with the clarity of an engineer's calm explanation of how something technical actually works. Here are the detailed how-to stories of many members of the first generation of open government pioneers, written in a generous, accessible style; this compilation presents us with a great deal to admire, ample provocation, and wise guidance from a group of remarkable individuals." -Susan Crawford, author of Captive Audience "Just as he did during his time in my administration, Goldstein has brought together industry leaders to discuss issues of relevance in the open data movement and the practical implications of implementing these policies... This book will help continue the work to make open government a reality across the country." - Mayor Rahm Emanuel, City of Chicago "A must-read for anyone who is passionate about what open data can do to transform city living." - Boris Johnson, Mayor of London




Healthcare Knowledge Management


Book Description

This unique text is a practical guide to managing and developing Healthcare Knowledge Management (KM) that is underpinned by theory and research. It provides readers with an understanding of approaches to the critical nature and use of knowledge by investigating healthcare-based KM systems. Designed to demystify the KM process and demonstrate its applicability, this text offers contemporary and clinically-relevant lessons for future organizational implementations.




Data-Driven Business Intelligence Systems for Socio-Technical Organizations


Book Description

The convergence of modern technology and social dynamics have shaped the very fabric of today’s organizations, making the role of Business Intelligence (BI) profoundly significant. Data-Driven Business Intelligence Systems for Socio-Technical Organizations delves into the heart of this transformative realm, offering an academic exploration of the tools, strategies, and methodologies that propel enterprises toward data-driven decision-making excellence. Socio-technical organizations, with their intricate interplay between human and technological components, require a unique approach to BI. This book embarks on a comprehensive journey, revealing how BI tools empower these entities to decipher the complexities of their data landscape. From user behavior to social interactions, technological systems to environmental factors, this work sheds light on the multifaceted sources of information that inform organizational strategies. Decision-makers within socio-technical organizations leverage BI insights to discern patterns, spot trends, and uncover correlations that influence operations and the intricate social dynamics within their entities. Research covering real-time monitoring and predictive analytics equips these organizations to respond swiftly to demands and anticipate future trends, harnessing the full potential of data. The book delves into their design, development, and architectural nuances, illuminating these concepts through case studies. This book is ideal for business executives, entrepreneurs, data analysts, marketers, government officials, educators, and researchers.