This book describes the emerging point-of-care (POC) technologies that are paving the way to the next generation healthcare monitoring and management. It provides the readers with comprehensive, up-to-date information about the emerging technologies, such as smartphone-based mobile healthcare technologies, smart devices, commercial personalized POC technologies, paper-based immunoassays (IAs), lab-on-a-chip (LOC)-based IAs, and multiplex IAs. The book also provides guided insights into the POC diabetes management software and smart applications, and the statistical determination of various bioanalytical parameters. Additionally, the authors discuss the future trends in POC technologies and personalized and integrated healthcare solutions for chronic diseases, such as diabetes, stress, obesity, and cardiovascular disorders. Each POC technology is described comprehensively and analyzed critically with its characteristic features, bioanalytical principles, applications, advantages, limitations, and future trends. This book would be a very useful resource and teaching aid for professionals working in the field of POC technologies, in vitro diagnostics (IVD), mobile healthcare, Big Data, smart technology, software, smart applications, biomedical engineering, biosensors, personalized healthcare, and other disciplines.

This book unravels the role of Point-of-Care (POC) glucose monitoring as an essential part of diabetes management. It provides the reader with an in-depth knowledge and understanding of diabetes management, including: the need for POC glucose monitoring the glucose detection technologies (invasive, noninvasive and continuous) being used in the POC devices the analytical performance, characteristics, pros and cons of the POC devices developed to date the importance and role of glycated hemoglobin (HbA1c) monitoring for diabetes management the various POC devices and analyzers for the determination of HbA1c. This is the first book to provide complete up-to-date information on POC glucose detection technologies and devices for diabetic monitoring and management. It will be an important reference for healthcare professionals, biomedical engineers, researchers, economists and policy makers. This book also serves as an asset and teaching aid for professionals and researchers in diabetic monitoring and management.

Scale up and implementation of new point-of-care (POC) diagnostics is a global health priority to enable the adoption of new evidence-based POC diagnostics and to replicate and extend the reach of POC diagnostics. Global private and public sector agencies have significantly increased their investment in the development of POC diagnostics to meet the unmet needs of patients in resource-limited settings, particularly disease burdened settings with limited access to laboratory infrastructure. However, previous research has demonstrated that the availability of health technologies in these settings does not always guarantee patient-centered outcomes. The applicability, effectiveness and sustainability of diagnostic technologies is affected by the involvement of all stakeholders during planning and implementation, which must be relevant to each specific context and sensitive to local culture. Factors such as infrastructure, resources, values and characteristics of participants can influence the implementation, scalability and sustainability of health interventions such as POC diagnostics. This book, "Implementation and Scale up of Point of Care (POC) Diagnostics in Resource-Limited Settings", presents literature reviews and primary research studies focusing on the implementation and scale up of POC diagnostics in resource-limited settings.

Medical Biosensors for Point of Care (POC) Applications discusses advances in this important and emerging field which has the potential to transform patient diagnosis and care. Part 1 covers the fundamentals of medical biosensors for point-of-care applications. Chapters in part 2 go on to look at materials and fabrication of medical biosensors while the next part looks at different technologies and operational techniques. The final set of chapters provide an overview of the current applications of this technology. Traditionally medical diagnostics have been dependent on sophisticated technologies which only trained professionals were able to operate. Recent research has focused on creating point-of-care diagnostic tools. These biosensors are miniaturised, portable, and are designed to be used at the point-of-care by untrained individuals, providing real-time and remote health monitoring. Provides essential knowledge for designers and manufacturers of biosensors for point-of-care applications Provides comprehensive coverage of the fundamentals, materials, technologies, and applications of medical biosensors for point-of-care applications Includes contributions from leading international researchers with extensive experience in developing medical biosensors Discusses advances in this important and emerging field which has the potential to transform patient diagnosis and care

Due to the simplicity, relative accuracy, fast result reporting, and user-friendliness of lateral flow immunoassay, its use has undergone tremendous growth in the diagnostic industry in the last few years. Such technology has been utilized widely and includes pregnancy and woman's health determination, cardiac and emergency conditions monitoring and testing, infectious disease including Flu screening, cancer marker screening, and drugs abuse testing. This book covers the scope of utilization, the principle of the technology, the patent concerns, information on the development and production of the test device and specific applications will be of interest to the diagnostic industry and the general scientific community.

This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.

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