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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
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.
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
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.
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.
The Future of Work in Asia and Beyond presents the findings and associated implications arising from a collaborative research study conducted on the potential impact of the Fourth Industrial Revolution (4IR – or Industry 4.0) on the labour markets, occupations and associated future workforce competencies and skills across ten countries. The 4IR concerns the digital transformation in society and business – an interface between technologies in the physical, digital and biological disciplines. The book explores many related issues: the nature of the 4IR, as well as demographic, generational and socio-cultural issues, economic and political perspectives, public and private sector similarities and differences, business strategy and managerial implications, human resource management/planning strategies, policies and practices, industry innovations, ‘best practice’ cases and comparative country studies. Chapters are based on a framework which combines labour market and multiple stakeholder theories. Issues are explored through the perceptions of organisational managers based in Australia, China, India, Indonesia, Malaysia, Mauritius, Nepal, Singapore, Taiwan and Thailand to provide an analysis of organisational, industry and government preparedness for the 4IR. This book is recommended reading for anyone wanting to gain an understanding of the 4IR and a range of related challenges and issues, as well as suggested strategies for governments, education and industry that are necessary to address them.
There is a significant deficiency among contemporary medicine practices reflected by experts making medical decisions for a large proportion of the population for which no or minimal data exists. Fortunately, our capacity to procure and apply such information is rapidly rising. As medicine becomes more individualized, the implementation of health IT and data interoperability become essential components to delivering quality healthcare. Quality Assurance in the Era of Individualized Medicine is a collection of innovative research on the methods and utilization of digital readouts to fashion an individualized therapy instead of a mass-population-directed strategy. While highlighting topics including assistive technologies, patient management, and clinical practices, this book is ideally designed for health professionals, doctors, nurses, hospital management, medical administrators, IT specialists, data scientists, researchers, academicians, and students.
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.